Optimization of the structural design of asphalt pavements for streets and highways

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dc.contributor.advisorGarcia Orozco, Francisco Javier
dc.contributor.authorVásquez-Varela, Luis Ricardo
dc.contributor.cvlacVÁSQUEZ-VARELA, Luis Ricardo [0001440367]spa
dc.contributor.googlescholarLuis Ricardo Vásquez-Varela [https://0-scholar-google-com.brum.beds.ac.uk/citations?hl=en&user=GPo84EoAAAAJ]spa
dc.contributor.orcidLuis Ricardo Vásquez-Varela [0000-0003-2293-7294]spa
dc.contributor.researchgateLuis R. Vásquez-Varela [https://www.researchgate.net/profile/Luis-Vasquez-Varela]spa
dc.contributor.researchgroupGestión de la Infraestructura de Transporte y del Espacio Públicospa
dc.date.accessioned2023-01-16T16:51:50Z
dc.date.available2023-01-16T16:51:50Z
dc.date.issued2022
dc.descriptiongráficos, tablasspa
dc.description.abstractThe construction of asphalt pavements in streets and highways is an activity that requires optimizing the consumption of significant economic and natural resources. Pavement design optimization meets contradictory objectives according to the availability of resources and users’ needs. This dissertation explores the application of metaheuristics to optimize the design of asphalt pavements using an incremental design based on the prediction of damage and vehicle operating costs (VOC). The costs are proportional to energy and resource consumption and polluting emissions. The evolution of asphalt pavement design and metaheuristic optimization techniques on this topic were reviewed. Four computer programs were developed: (1) UNLEA, a program for the structural analysis of multilayer systems. (2) PSO-UNLEA, a program that uses particle swarm optimization metaheuristic (PSO) for the backcalculation of pavement moduli. (3) UNPAVE, an incremental pavement design program based on the equations of the North American MEPDG and includes the computation of vehicle operating costs based on IRI. (4) PSO-PAVE, a PSO program to search for thicknesses that optimize the design considering construction and vehicle operating costs. The case studies show that the backcalculation and structural design of pavements can be optimized by PSO considering restrictions in the thickness and the selection of materials. Future developments should reduce the computational cost and calibrate the pavement performance and VOC models. (Texto tomado de la fuente)eng
dc.description.abstractLa construcción de pavimentos asfálticos en calles y carreteras es una actividad que requiere la optimización del consumo de cuantiosos recursos económicos y naturales. La optimización del diseño de pavimentos atiende objetivos contradictorios de acuerdo con la disponibilidad de recursos y las necesidades de los usuarios. Este trabajo explora el empleo de metaheurísticas para optimizar el diseño de pavimentos asfálticos empleando el diseño incremental basado en la predicción del deterioro y los costos de operación vehicular (COV). Los costos son proporcionales al consumo energético y de recursos y las emisiones contaminantes. Se revisó la evolución del diseño de pavimentos asfálticos y el desarrollo de técnicas metaheurísticas de optimización en este tema. Se desarrollaron cuatro programas de computador: (1) UNLEA, programa para el análisis estructural de sistemas multicapa. (2) PSO-UNLEA, programa que emplea la metaheurística de optimización con enjambre de partículas (PSO) para el cálculo inverso de módulos de pavimentos. (3) UNPAVE, programa de diseño incremental de pavimentos basado en las ecuaciones de la MEPDG norteamericana, y el cálculo de costos de construcción y operación vehicular basados en el IRI. (4) PSO-PAVE, programa que emplea la PSO en la búsqueda de espesores que permitan optimizar el diseño considerando los costos de construcción y de operación vehicular. Los estudios de caso muestran que el cálculo inverso y el diseño estructural de pavimentos pueden optimizarse mediante PSO considerando restricciones en los espesores y la selección de materiales. Los desarrollos futuros deben enfocarse en reducir el costo computacional y calibrar los modelos de deterioro y COV.spa
dc.description.curricularareaEléctrica, Electrónica, Automatización Y Telecomunicacionesspa
dc.description.degreelevelDoctoradospa
dc.description.degreenameDoctor en Ingeniería - Ingeniería Automáticaspa
dc.description.researchareaDiseño incremental de pavimentosspa
dc.format.extentxxx, 259 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/82943
dc.language.isoengspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Manizalesspa
dc.publisher.facultyFacultad de Ingeniería y Arquitecturaspa
dc.publisher.placeManizales, Colombiaspa
dc.publisher.programManizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - Automáticaspa
dc.relation.referencesAASHTO. (1993). AASHTO Guide for Design of Pavement Structures. Washington, D.C.: American Association of State Highway and Transportation Officials.spa
dc.relation.referencesAASHTO. (2008). Mechanistic-Empirical Pavement Design Guide. A Manual of Practice - Interim Edition. Washington D.C.: American Association of State Highway and Transportation Officials.spa
dc.relation.referencesAbu-Lebdeh, G., Chen, H., & Ghanim, M. (2014). Improving Performance of Genetic Algorithms for Transportation Systems: Case of Parallel Genetic Algorithms. Journal of Infrastructure Systems, 1-8.spa
dc.relation.referencesAhlborn, G. (1972). ELSYM5, Computer Program for Determining Stresses and Deformations in Five Layer Elastic Systems. Berkeley: University of California.spa
dc.relation.referencesAhlvin, R. G., & Ulery, H. H. (1962). Tabulated Values for Determining the Complete Pattern of Stresses, Strains, and Deflections Beneath a Uniform Circular Load on a Homogeneous Half-Space. Highway Research Board Bulletin, 342, 1-13. Retrieved from http://onlinepubs.trb.org/onlinepubs/hrbbulletin/342/342-001.pdfspa
dc.relation.referencesAhmed, K., Al-Khateeb, B., & Mahmood, M. (2018). A Chaos with Discrete Multiobjective Particle Swarm Optimization for Pavement Maintenance. Journal of Theoretical and Applied Information Technology, 96(8), 2317-2326.spa
dc.relation.referencesAlae, M., Yanqing, Z., Zarei, S., Fu, G., & Cao, D. (2018). Effects of layer interface conditions on top-down fatigue cracking of asphalt pavements. International Journal of Pavement Engineering, 1-9.spa
dc.relation.referencesAlarcón-Guzmán, A. (2004). The geotechnical problem (In Spanish). Class notes of the "Soil Behavior" course in the Master of Geotechnical Engineering. Bogotá, Cundinamarca, Colombia.spa
dc.relation.referencesAli, H. A., & Shiraz, D. T. (1998). Mechanistic Evaluation of Test Data from LTPP Flexible Pavement Test Sections Publication No. FHWA-RD-98-012. McLean, VA: Federal Highway Administration.spa
dc.relation.referencesAlkasawneh, W. (2007). Backcalculation of Pavement Moduli Using Genetic Algorithms. Akron, Ohio, USA: The University of Akron.spa
dc.relation.referencesAl-Omari, B., & Darter, M. (1994). Relationships Between International Roughness Index and Present Serviceability Rating. Transportation Research Record 1435, 130-136.spa
dc.relation.referencesAl-Qadi, I. L., & Wang, H. (2009). Evaluation of Pavement Damage due to New Tire Designs Research Report ICT-09-048. Illinois Center for Transportation.spa
dc.relation.referencesAl-Rumahiti, A. (2021, November 21). Multi-layer Elastic Analysis. Retrieved from Mathworks: https://la.mathworks.com/matlabcentral/fileexchange/69465-multi-layer-elastic-analysisspa
dc.relation.referencesAMADEUS. (2000). AMADEUS - Advanced Models for Analytical Design of European Pavement Structures.spa
dc.relation.referencesAnderson, M. (1990). Backcalculation of Composite Pavement Layer Moduli - Technical Report GL-90-15. Vicksburg, Mississippi: US Army Corps of Engineers.spa
dc.relation.referencesAsphalt Institute. (1981). Thickness Design—Asphalt Pavements for Highways and Streets. Manual Series No. 1 (Ninth ed.). Lexington, Kentucky, USA: Asphalt Institute.spa
dc.relation.referencesAsphalt Institute. (1982). Research and Development of the Asphalt Institute´s Thickness Design Manual (MS-1) Ninth Edition. Lexington, Kentucky, USA: Asphalt Institute.spa
dc.relation.referencesAsphalt Institute. (2000). Asphalt Overlays for Highway and Street Rehabilitation Manual MS-17. Lexington, Kentucky: Asphalt Institute.spa
dc.relation.referencesAsphalt Institute. (2005). SW-1 Asphalt Pavement Thickness Design Software for Highways, Airports, Heavy Wheel Loads and Other Applications User´s Guide. Lexington, Kentucky, USA: Asphalt Institute.spa
dc.relation.referencesAustroads. (1992). Pavement Design - A Guide to the Structural Design of Road Pavements (Vols. AP-17/92). Sydney, Australia: Australian Road Research Board.spa
dc.relation.referencesAustroads. (1994). Pavement Design - A Guide to the Structural Design of Road Pavements. Interim Version of Revised Overlay Design Procedures. Sydney, Australia: Austroads Pavement Research Group.spa
dc.relation.referencesBabkov, V., & Zamakhayev, M. (1967). Highway Engineering. Moscow, USSR: Mir publishers.spa
dc.relation.referencesBaus, R. L., & Stires, N. R. (2010). Mechanistic-Empirical Pavement Design Guide Implementation. Columbia, South Carolina: Department of Civil and Environmental Engineering - The University of South Carolina.spa
dc.relation.referencesBosurgi, G., & Trifirò, F. (2005). A Model Based on Artificial Neural Networks and Genetic Algorithms for Pavement Maintenance Management. The International Journal of Pavement Engineering, 6(3), 201-209.spa
dc.relation.referencesBrown, S. F. (1967). Stresses and deformations in flexible layered pavement systems subjected to dynamic loads, Ph.D. Thesis. Nottingham, UK: The University of Nottingham. Retrieved from http://eprints.nottingham.ac.uk/11667/1/520241.pdfspa
dc.relation.referencesBrown, S. F. (1973). Determination of Young's modulus for Bituminous Materials in Pavement Design. Highway Research Record 431. 52nd Annual Meeting of the Highway Research Board (pp. 38-49). Washington D.C.: Highway Research Board.spa
dc.relation.referencesBrown, S. F. (1993). Soil Mechanics in Pavement Engineering. Géotechnique, 46(3), 383-426.spa
dc.relation.referencesBrown, S. F., & Pappin, J. W. (1981). Analysis of Pavements with Granular Bases. Transportation Research Record 810, 17-22.spa
dc.relation.referencesBrown, S. F., Bunton, J. M., & Pell, P. S. (1982). The Development and Implementation of Analytical Pavement Design for British Conditions. Proceedings Fifth International Conference on the Structural Design of Asphalt Pavements (pp. 17-44). University of Michigan and Delft University of Technology.spa
dc.relation.referencesBrunton, J. M., & D'Almeida, J. R. (1992). Modeling Material Non-Linearity in a Pavement Back-Calculation Procedure. Transportation Research Record 1377, 99-106.spa
dc.relation.referencesBurmister, D. M. (1943). The Theory of Stresses and Displacements in Layered Systems and Application to Design of Airport Runways. Proc. HRB (pp. 120-125). Washington D.C.: Highway Research Board.spa
dc.relation.referencesCai, Y., Sangghaleh, A., & Pan, E. (2015). Effect of anisotropic base/interlayer on the mechanistic responses of layered pavements. Computer and Geotechnics, 65, 250-257.spa
dc.relation.referencesCao, W., Norouzi, A., & Kim, Y. R. (2016). Application of Viscoelastic Continuum Damage Approach to Predict Fatigue Performance of Binzhou Perpetual Pavements. Journal of Traffic and Transportation Engineering (English Edition), 3(2), 104-115. doi:http://dx.doi.org/10.1016/j.jtte.2016.03.002spa
dc.relation.referencesCDKN. (2012). Critical Climate Change Concerns for the Road Sector in Colombia. Bogotá: Climate Development and Knowledge Network.spa
dc.relation.referencesCentral Intelligence Agency. (2013). The World Factbook 2013-2014. Retrieved March 24, 2016, from https://www.cia.gov/library/publications/the-world-factbook/index.htmlspa
dc.relation.referencesCercevik, A. E., Bozkurt, H., & Toklu, Y. C. (2014). Applications of meta-heuristic algorithms to civil engineering problems, a survey. In Y. C. Toklu, & G. Bekdas (Ed.), Metaheuristics and Engineering - 14th Workshop of the EURO Working Group (pp. 63-65). Istambul: The Association of European Operational Research Societies.spa
dc.relation.referencesCeylan, H., Kim, S., Gopalakrishnan, K., & Ma, D. (2013). Iowa Calibration of MEPDG Performance Prediction Models - Final Report. Iowa State University. Ames, Iowa: Institute for Transportation.spa
dc.relation.referencesChan, W. T., Fwa, T. F., & Hoque, K. Z. (2001). Constraint Handling Methods in Pavement Maintenance Programming. Transportation Research Part C, 9, 175-190.spa
dc.relation.referencesChan, W. T., Fwa, T. F., & Tan, C. Y. (1994). Road-Maintenance Planning Using Genetic Algorithms. I: Formulation. Journal of Transportation Engineering, 120(5), 693-709.spa
dc.relation.referencesChang, J.-R. (2013). Particle Swarm Optimization Method for Optimal Prioritization of Pavement Sections for Maintenance and Rehabilitation Activities. Applied Mechanics and Materials, 343, 43-49.spa
dc.relation.referencesChang, J.-R., & Chao, S.-J. (2010). Pavement Maintenance and Rehabilitation Decisions Derived by Genetic Programming. 2010 Sixth International Conference on Natural Computation ICNC (pp. 2439-2443). IEEE.spa
dc.relation.referencesCharyulu, M. K. (1964). Theoretical stress distribution in an elastic multi-layered medium. Iowa State University. Ames, Iowa: Retrospective Theses and Dissertations 2730.spa
dc.relation.referencesChatti, K., & Yun, K. K. (1996). SAPSI-M: A Computer Program for Analyzing Asphalt Concrete Pavements under Moving Arbitrary Loads. (T. R. Board, Ed.) Transportation Research Record 1539.spa
dc.relation.referencesChatti, K., & Zaabar, I. (2012). NCHRP Report 720 Estimating the Effects of Pavement Condition on Vehicle Operating Costs. Washington D.C.: Transportation Research Board.spa
dc.relation.referencesChen, D.-H., Zaman, M., Laguros, J., & Soltani, A. (1985). Assessment of Computer Programs for Analysis of Flexible Pavement Structure. Transportation Research Record 1482, 123-133.spa
dc.relation.referencesChen, W. T. (1971). Computation of Stresses and Displacements in a Layered Elastic Medium. International Journal of Engineering Science, 775-800.spa
dc.relation.referencesCheu, R. L., Wang, Y., & Fwa, T. F. (2004). Genetic Algorithm-Simulation Methodology for Pavement Maintenance Scheduling. Computer-Aided Civil and Infrastructure Engineering, 19, 446-455.spa
dc.relation.referencesCho, Y. H., McCullough, B. F., & Weismann, J. (1996). Considerations on Finite-Element Method Application in Pavement Structural Analysis. Transportation Research Record: Journal of the Transportation Research Board, 1539(1), 96-101.spa
dc.relation.referencesChoi, J. W., Wu, R., Pestana, J. M., & Harvey, J. (2010). New Layer-Moduli Back-Calculation Method Based on the Constrained Extended Kalman Filter. Journal of Transportation Engineering, 136(1), 20-30.spa
dc.relation.referencesChong, D., Wang, Y., Dai, Z., Chen, X., Wang, D., & Oeser, M. (2018). Multiobjective Optimization of Asphalt Pavement Design and Maintenance Decisions Based on Sustainability Principles and Mechanistic-Empirical Pavement Analysis. International Journal of Sustainable Transportation, 12(6), 461-472.spa
dc.relation.referencesChootinan, P., Chen, A., Horrocks, M. R., & Bolling, D. (2006). A Multi-Year Pavement Maintenance Program Using a Stochastic Simulation-Based Genetic Algorithm Approach. Transportation Research Part A, 40, 725-743.spa
dc.relation.referencesChristensen, P. W., & Klarbring, A. (2009). An Introduction to Structural Optimization. Linköping, Sweden: Springer Science + Bussiness Media B. V.spa
dc.relation.referencesClerc, M. (1999). The Swarm and the Queen: Towards a Deterministic and Adaptative Particle Swarm Optimization. Proceedings of the Congress on Evolutionary Computing, III, pp. 1951-1957.spa
dc.relation.referencesClimate Analytics. (2022). PROVIDE climate risk dashboard. Retrieved from https://climate-risk-dashboard.climateanalytics.org/spa
dc.relation.referencesColeri, E., Guler, M., Gungor, A. G., & Harvey, J. T. (2010). Prediction of Subgrade Resilient Modulus Using Genetic Algorithm and Curve-Shifting Methodology. Transportation Research Record: Journal of the Transportation Research Board, 2170, 67-73.spa
dc.relation.referencesCorté, J.-F., & Goux, M.-T. (1996, January). Design of Pavements Structures: The French Technical Guide. Transportation Research Record: Journal of the Transportation Research Board(1539), 116-124. doi:10.3141/1539-16spa
dc.relation.referencesCroney, D., & Croney, P. (1998). The design and performance of road pavements (Third ed.). London, UK: McGraw-Hill.spa
dc.relation.referencesCunha Coelho, N. F. (2016). Calibration of MEPDG Performance Models for Flexible Pavement Distresses to Local Conditions of Ontario - M.Sc. Thesis. The University of Texas at Arlington. Arlington, Texas: The University of Texas at Arlington.spa
dc.relation.referencesDalla Valle, P., & Thom, N. (2016a). Improvement of method of equivalent thicknesses (MET) for calculation of critical strains for flexible pavements. International Journal of Pavement Engineering, 1-8.spa
dc.relation.referencesDalla Valle, P., & Thom, N. (2016b). Reliability in pavement design. E & E Congress 6th Eurasphalt & Eurobitume Congress. Prague, Czech Republic.spa
dc.relation.referencesDarter, M. I., & Hudson, W. R. (1973). Probabilistic Design Concepts Applied to Flexible Pavement System Design - Research Report 123-18. Texas Highway Department. Austin, Texas: Center for Highway Research - The University of Texas at Austin.spa
dc.relation.referencesDauzats, M., & Rampal, A. (1988). Mécanismes de fissuration de surface des couches de roulement. Bulletin de Liaison des Laboratoires des Ponts et Chaussés, 154, 57-72.spa
dc.relation.referencesDe Jong, D., Peutz, M. G., & Korswagen, A. R. (1979). Computer program BISAR, layered systems under normal and tangential surface loads. Amsterdam: Koninklijke/Shell Laboratorium, Shell Research B.V.spa
dc.relation.referencesDede, T., Kripka, M., Togan, V., Yepes, V., & Rao, R. V. (2019). Usage of Optimization Techniques in Civil Engineering During the Last Two Decades. Current Trends in Civil & Structural Engineering, 2(1), 1-17.spa
dc.relation.referencesDeshpande, V. P., Damnjanovic, I. D., & Gardoni, P. (2010). Reliability-Based Optimization Models for Scheduling Pavement Rehabilitation. Computer-Aided Civil and Infrastructure Engineering, 25, 227-237.spa
dc.relation.referencesDi Mino, G., De Blasiis, M. R., Di Noto, F., & Noto, S. (2013). An Advanced Pavement Management System based on a Genetic Algorithm for a Motorway Network. In Y. Tsompanakis (Ed.), Proceedings of the Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering (pp. 1-17). Stirlingshire, Scotland: Civil-Comp Press.spa
dc.relation.referencesDilip, D. M., & Sivakumar Babu, G. L. (2013). Methodology for Pavement Design Reliability and Back Analysis Using Markov Chain Monte Carlo Simulation. ASCE Journal of Transportation Engineering, 139(1), 65-74.spa
dc.relation.referencesDilip, D. M., & Sivakumar Babu, G. L. (2021). Reliability-Based Design Optimization of Flexible Pavements Using Kriging Models. Journal of Transportation Engineering. Part B: Pavements, 04021046 1-14.spa
dc.relation.referencesDilip, D. M., Ravi, P., & Sivakumar Babu, G. L. (2013). System Reliability Analysis of Flexible Pavements. ASCE Journal of Transportation Engineering, 139(10), 1001-1009.spa
dc.relation.referencesDinegdae, Y. H., & Birgisson, B. (2016). Reliability-Based Design Procedure for Fatigue Cracking in Asphalt Pavements. Transportation Research Record: Journal of the Transportation Research Board, 2583(1), 127-133.spa
dc.relation.referencesDinegdae, Y., Onifade, I., Birgisson, B., Lytton, R., & Little, D. (2018). Towards a Reliability-Based Pavement Design using Response Surface Methods. Transportation Research Record, 2672(40), 97-107.spa
dc.relation.referencesDiwekar, U. (2008). Introduction to Applied Optimization. Clarendon Hils, IL: Springer Science + Business Media, LLC.spa
dc.relation.referencesDuncan, J. M., Monismith, C. L., & L., W. E. (1968). Finite Element Analyses of Pavements. Highway Research Record, 228, 18-33.spa
dc.relation.referencesDuong, N. S., Blanc, J., & Hornych, P. (2017). Analysis of the behavior of pavement layers interfaces from in situ measurements. In A. Loizos, I. L. Al-Qadi, & T. Scarpas (Ed.), 10th International Conference on the Bearing Capacity of Roads, Railways, and Airfields (BCRRA 2017). Athens, Greece: CRC Press.spa
dc.relation.referencesElhadidy, A. A., Elbeltagi, E. E., & Ammar, M. A. (2015). Optimum Analysis of Pavement Maintenance Using Multi-Objective Genetic Algorithms. Housing and Building National Research Center HBRC Journal, 107-113.spa
dc.relation.referencesERDC. (2002). WinLEA ERDC Developed Software WinJULEA Windows Layered Elastic Analysis. GSL - Airfields & Pavements Branch. Vicksburg, Mississippi: Engineering Research & Development Center.spa
dc.relation.referencesErlingsson, S., & Ahmed, A. (2013). Fast layered elastic response program for the analysis of flexible pavement structures. Road Materials and Pavement Design, 14(1), 196-210. doi:10.1080/14680629.2012.757558spa
dc.relation.referencesFarhan, J., & Fwa, T. F. (2012). Incorporating Priority Preferences into Pavement Maintenance Programming. Journal of Transportation Engineering, 138(6), 714-722.spa
dc.relation.referencesFederal Aviation Administration. (1995). Airport Pavement and Evaluation - Advisory Circular AC 150/5320-6D (Cancelled). Washington, D.C.: U.S. Department of Transportation - Federal Aviation Administration.spa
dc.relation.referencesFerreira, A., Antunes, A., & Picado-Santos, L. (2002). Probabilistic Segment-linked Pavement Management Optimization Model. Journal of Transportation Engineering, 128(6), 568-577.spa
dc.relation.referencesFigueroa, A., Reyes, F., Hernández, D., Jiménez, C., & Bohórquez, N. (2007). Análisis de un asfalto modificado con icopor y su incidencia en una mezcla asfáltica densa en caliente. Ingeniería e Investigación, 27(3), 5-15.spa
dc.relation.referencesFinn, F. N., Saraf, C., Kulkarni, R., Nair, K., Smith, W., & Abdullah, A. (1977). The Use of Distress Prediction Subsystems in the Design of Pavement Structures. Proceedings Fourth International Conference on the Structural Design of Asphalt Pavements. 1, pp. 3-38. Michigan: The University of Michigan.spa
dc.relation.referencesFlintsch, G. W., & Chen, C. (2004). Soft Computing Applications in Infrastructure Management. Journal of Infrastructure Systems, 10(4), 157-165.spa
dc.relation.referencesFreeman, R. B., & Harr, M. E. (2004). Stress Predictions for Flexible Pavement Systems. Journal of Transportation Engineering, 130(495-502).spa
dc.relation.referencesFwa, T. F., Chan, T. Y., & Hoque, K. Z. (1998). Analysis of Pavement Management Activities Programming by Genetic Algorithms. Transportation Research Record: Journal of the Transportation Research Board, 1643, 1-6.spa
dc.relation.referencesFwa, T. F., Chan, W. T., & Hoque, K. Z. (2000). Multiobjective Optimization for Pavement Maintenance Programming. Journal of Transportation Engineering, 126(5), 367-374.spa
dc.relation.referencesFwa, T. F., Chan, W. T., & Tan, C. Y. (1994). Optimal Programming by Genetic Algorithm for Pavement Management. Transportation Research Record: Journal of the Transportation Research Board, 1455, 31-41.spa
dc.relation.referencesFwa, T. F., Chan, W. T., & Tan, C. Y. (1996). Genetic-Algorithm Programming of Road Maintenance and Rehabilitation. Journal of Transportation Engineering, 122(3), 246-253.spa
dc.relation.referencesFwa, T. F., Tan, C. Y., & Chan, W. T. (1997). Backcalculation Analysis of Pavement-Layer Moduli Using Genetic Algorithms. Transportation Research Record: Journal of the Transportation Research Board, 1570, 134-142.spa
dc.relation.referencesGallego, R., Toro, E., & Escobar, A. (2015). Técnicas Heurísticas y Metaheurísticas. Pereira, Colombia: Universidad Tecnológica de Pereira.spa
dc.relation.referencesGandomi, A. H., Yang, X.-S., Talatahari, S., & Alavi, A. H. (2013). Metaheuristic Algorithms in Modeling and Optimization. In A. H. Gandomi, X.-S. Yang, S. Talatahari, & A. H. Alavi, Metaheuristics Applications in Structures and Infrastructures (pp. 1-24). Elsevier Science & Technology.spa
dc.relation.referencesGao, L., Xie, C., Zhang, Z., & Waller, S. T. (2012). Network-Level Road Pavement Maintenance and Rehabilitation Scheduling for Optimal Performance Improvement and Budget Utilization. Computer-Aided Civil and Infrastructure Engineering, 27, 276-287.spa
dc.relation.referencesGarnica Anguas, P., & Hernández Domínguez, R. (2013). Manual de Usuario IMT-PAVE 1.1 Documento Técnico No. 53. Sanfandila, Qro: Instituto Mexicano del Transporte.spa
dc.relation.referencesGhanizadeh, A. R. (2016). An Optimization Model for Design of Asphalt Pavements Based on IHAP Code Number 234. Advances in Civil Engineering, 1-8.spa
dc.relation.referencesGhanizadeh, A. R. (2017). Application of support vector machine regression for predicting critical responses of flexible pavements. International Journal of Transportation Engineering, 4(4), 305-315.spa
dc.relation.referencesGhanizadeh, A. R., & Ziaie, A. (2015). NonPAS: A Program for Nonlinear Analysis of Flexible Pavements. International Journal of Integrated Engineering, 7(1), 21-28.spa
dc.relation.referencesGhanizedeh, A. R., & Ahadi, M. R. (2015). Application of Artificial Neural Networks for Analysis of Flexible Pavements under Static Loading of Standard Axle. International Journal of Transportation Engineering, 3(1), 31-43.spa
dc.relation.referencesGolroo, A., & Tighe, S. L. (2012). Optimum Genetic Algorithm Structure Selection in Pavement Management. Asian Journal of Applied Sciences, 5(6), 327-341.spa
dc.relation.referencesGonzales, C. R., Barker, W. R., & Bianchini, A. (2012). Reformulation of the CBR procedure. Report I: Basic report. U.S. Army Corps of Engineers, Geotechnical and Structures Laboratory. Vicksburg: U.S. Army Engineer Research and Development Center.spa
dc.relation.referencesGonzalez, C. R. (2015). Development and Validation of a Stress-Based Procedure for the Design of Military Flexible Pavements (Ph.D. Thesis). The University of Illinois at Urbana-Champaign. Urbana, Ilinois: The University of Illinois at Urbana-Champaign.spa
dc.relation.referencesGopalakrishnan, K. (2009). Backcalculation of Pavement Moduli Using Bio-Inspired Hybrid Metaheuristics and Cooperative Strategies. Proceedings of the 2009 Mid-Continent Transportation Research Symposium (pp. 1-5). Ames, Iowa: Iowa State University.spa
dc.relation.referencesGopalakrishnan, K. (2010). Neural Network-Swarm Intelligence Hybrid Nonlinear Optimization Algorithm for Pavement Moduli Back-Calculation. Journal of Transportation Engineering, 136(6), 528-536.spa
dc.relation.referencesGranada Echeverri, M. (2009). Algoritmos Evolutivos y Técnicas Bioinspiradas. De la Teoría a la Práctica. Pereira, Colombia: Universidad Tecnológica de Pereira.spa
dc.relation.referencesGudipudi, P. P., Underwood, B. S., & Zalghout, A. (2017). Impact of climate change on pavement structural performance in the United States. Transportation Research Part D: Transport and Environment, 57, 172-184. doi:https://doi.org/10.1016/j.trd.2017.09.022spa
dc.relation.referencesHaas, R., Tighe, S., Dore, G., & Hein, D. (2007). Mechanistic-Empirical Pavement Design: Evolution and Future Challenges. 2007 Annual Conference Transportation Association of Canada, (pp. 1-23). Saskatoon, Saskatchewan.spa
dc.relation.referencesHadi, M. N., & Arfiadi, Y. (2001). Optimum rigid pavement design by genetic algorithms. Computers and Structures, 79, 1317-1624.spa
dc.relation.referencesHarr, M. E., & Lovell, Jr., C. W. (1963). Vertical Stresses Under Certain Axisymmetrical Loadings. Highway Research Record, 39, 68-81.spa
dc.relation.referencesHasan, M. M., Rahman, A. A., & Tarefder, R. A. (2018). Investigation of Accuracy of Pavement Mechanistic Empirical Prediction Performance by Incorporating Level 1 Inputs. Journal of Traffic and Transportation Engineering (English Edition), 1-10. doi: https://doi.org/10.1016/j.jtte.2018.06.006spa
dc.relation.referencesHayhoe, G. F. (2002). LEAF - A New Layered Elastic Computational Program for FAA Pavement Design and Evaluation Procedures. In F. A. Administration (Ed.), The 2002 Federal Aviation Administration Airport Technology Transfer Conference, (pp. 1-15).spa
dc.relation.referencesHe, Z., Cai, Y., & Haas, R. (1996). OPAC 2000 Engineering document. Ontario: Ministry of Transportation of Ontario.spa
dc.relation.referencesHerabat, P., & Tangphaisankun, A. (2005). Multi-Objective Optimization Model using Constraint-Based Genetic Algorithms for Thailand Pavement Management. Journal of the Eastern Asia Society for Transportation Studies, 6, 1137-1152.spa
dc.relation.referencesHorak, E., Maree, J. H., & van Wijk, A. J. (1989). Procedures for Using Impulse Deflectometer (IDM) Measurements in the Structural Evaluation of Pavements. Proceedings of the Annual Transportation Convention, 5A. Pretoria, South Africa.spa
dc.relation.referencesHu, K.-F., Jiang, K.-P., & Chang, D.-W. (2007). Study of Dynamic Backcalculation Program with Genetic Algorithms for FWD on Pavements. Tamkang Journal of Science and Engineering, 10(4), 297-305.spa
dc.relation.referencesHuang, Y. H. (1969). Computation of Equivalent Single-Wheel Loads Using Layered Theory. Highway Research Record(291), 144-155.spa
dc.relation.referencesHuang, Y. H. (1993). Pavement Analysis and Design (First ed.). Englewood Cliffs, NJ, USA: Prentice Hall.spa
dc.relation.referencesHuang, Y. H. (2004). Pavement Analysis and Design (Second ed.). Upper Saddle River, NJ, USA: Pearson Prentice Hall.spa
dc.relation.referencesHunaidi, O. (1998). Evolution-Based Genetic Algorithms for Analysis of Non-Destructive Surface Wave Tests on Pavements. NDT&E International, 31(4), 273-280.spa
dc.relation.referencesIDEAM. (23 de 01 de 2021). Consulta y Descarga de Datos Hidrometeorológicos. Obtenido de Consulta y Descarga de Datos Hidrometeorológicos: http://dhime.ideam.gov.co/atencionciudadano/spa
dc.relation.referencesINVÍAS. (2003). Operativo Móvil de Pesaje Carretera Manizales - Chinchiná en el sitio Cenicafé. Bogotá D.C.: Instituto Nacional de Vías. Subdirección de Conservación.spa
dc.relation.referencesINVÍAS. (2007). Manual de diseño de pavimentos asfálticos para vías con bajos volumenes de tránsito. Bogotá: Instituto Nacional de Vías.spa
dc.relation.referencesINVÍAS. (2011). Volumenes de Tránsito . Bogotá DC: Instituto Nacional de Vías de Colombia.spa
dc.relation.referencesIoannides, A. M., & Khazanovich, L. (1998). General Formulation for Multilayered Pavement Systems. Journal of Transportation Engineering, 124(1), 82-90.spa
dc.relation.referencesIPCC. (2014). Climate Change 2014-Impacts, Adaptation and Vulnerability: Regional Aspects. Intergovernmental Panel on Climate Change. Cambridge University Press. doi:https://doi.org/10.1017/CBO9781107415379spa
dc.relation.referencesJameson, G. W. (1996). Origins of AUSTROADS Design Procedures for Granular Pavements. Research Report ARR 292. Vermont South, Australia: ARRB Transport Research Ltd.spa
dc.relation.referencesJaved, F. (2011). Integrated Prioritization and Optimization Approach for Pavement Management. Ph.D. Thesis, Singapore.spa
dc.relation.referencesJoint Departments of the Army and Air Force. (1994). TM 5-822-13/AFJMAN 32-1018 Pavement Design for Roads, Streets and Open Storage Areas, Elastic Layered Method. Washington D.C.spa
dc.relation.referencesJooste, F. (2016, 07 12). Automated Backcalculation: How the backcalculation error is calculated. Retrieved 06 04, 2019, from Rubicon Toolbox: Rubicon forum: http://forum.rubicontoolbox.com/pages/topic7-how-the-backcalculation-error-is-calculated.aspxspa
dc.relation.referencesKai, W. (1987). Analysis and Calculation of Stresses and Displacements in Layered Elastic Systems. Acta Mechanica Sinica, 3(3), 252-260.spa
dc.relation.referencesKameyama, S., Himeno, K., Kasahara, K., & Maruyama, T. (1998). Backcalculation of Pavement Layer Moduli using Genetic Algorithms. 8th International Conference on Asphalt Pavements (pp. 1375-1385). Seattle, Washington: University of Washington.spa
dc.relation.referencesKasperick, T., & Ksabaiti, K. (2015). Calibration of the Mechanistic-Empirical Pavement Design Guide for Local Paved Roads in Wyoming. Department of Civil and Architectural Engineering - The University of Wyoming. Laramie, Wyoming: The Mountain Plains Consortium.spa
dc.relation.referencesKenis, W. J., Sherwood, J. A., & McMahon, R. F. (1982). Verification and Application of the VESYS Structural Subsystem. Proceedings Fifth International Conference on the Structural Design of Asphalt Pavements. 1, pp. 333-348. University of Michigan and Delft University of Technology.spa
dc.relation.referencesKennedy, J., & Eberhart, R. (1995). Particle Swarm Optimization. Proceedings of ICNN'95 - International Conference on Neural Networks (pp. 1942-1948). Perth, WA, Australia, Australia: IEEE. doi:10.1109/ICNN.1995.488968spa
dc.relation.referencesKhazanovich, L., & Wang, Q. (2007). MnLayer – A high performance layered elastic analysis program. Transportation Research Record: Journal of the Transportation Research Board(2037), 63-75.spa
dc.relation.referencesKim, H. B., & Lee, S. H. (2002). Reliability-Based Design Model Applied to Mechanistic Empirical Pavement Design. KSCE Journal of Civil Engineering, 6(3), 263-272.spa
dc.relation.referencesKim, M. (2007). Three-Dimensional Finite Element Analysis of Flexible Pavements Considering Nonlinear Pavement Foundation Behavior. The University of Illinois at Urbana - Champaign. Urbana, Illinois: The University of Illinois at Urbana - Champaign.spa
dc.relation.referencesKim, S. H., Little, D. N., & Masad, E. (2005). Simple methods to estimate inherent and stress-induced anisotropy of aggregate base. Transportation Research Record 1913, 24-31.spa
dc.relation.referencesKim, S., Ceylan, H., Ma, D., & Gopalakrishnan, K. (2014). Calibration of Pavement ME Design and Mechanistic-Empirical Pavement Design Guide Performance Prediction Models for Iowa Pavement Systems. (A. S. Engineers, Ed.) Journal of Transportation Engineering, 140(10).spa
dc.relation.referencesKim, Y. R., Jadoun, F. M., Hou, T., & Muthadi, N. (2011). Local Calibration of the MEPDG for Flexible Pavement Design - Report FHWA\NC\2007-07. Raleigh, NC: North Carolina Department of Transportation.spa
dc.relation.referencesKimura, T. (2014). Studies on Stress Distribution in Pavements Subjected to Surface Shear Loads. Proceedings of the Japanese Academy, 90(2), 47-55.spa
dc.relation.referencesKosasih, D. (2011). Back-Calculation of Pavement Modulus Values Using Genetic Algorithms. Proceedings of the Eastern Asia Society for Transportation Studies, 8.spa
dc.relation.referencesKruntcheva, M. R., Collop, A. C., & Thom, N. H. (2005). Effect of Bond Condition on Flexible Pavement Performance. Journal of Transportation Engineering, 131(11), 880-888.spa
dc.relation.referencesKuyu, Y. C., & Vatansever, F. (2021). Advanced Metaheuristic Algorithms on Solving Multimodal Functions: Experimental Analyses and Performance Evaluations. Archives of Computational Methods in Engineering.spa
dc.relation.referencesLamboll, R., Rogelj, J., & Schleussner, C. F. (2022). A guide to scenarios for the PROVIDE project. Earth and Space Science Open Archive.spa
dc.relation.referencesLaurent-Matamoros, P., Loría-Salazar, L.-G., Leiva-Padilla, P., & Trejos-Castillo, C. (2018). PITRA-BACK Herramienta de Cálculo para el Diseño de Sobrecapas Asfálticas de Pavimentos Flexibles en Costa Rica. Software version Beta 1.0.1. Costa Rica: Universidad de Costa Rica - Laboratorio Nacional de Materiales y Modelos Estructurales.spa
dc.relation.referencesLCPC - SETRA. (1994). Conception et dimensionnement des structures de chaussée - Guide technique. Paris, France: Laboratoire Central des Ponts et Chaussées - Service d'études sur les Transports, les Routes et leurs Aménagements.spa
dc.relation.referencesLea, J. (2014). About OpenPave.org. Retrieved 05 29, 2018, from OpenPave.org Open Source Pavement Engineering: http://www.openpave.org/spa
dc.relation.referencesLi, J., Uhlmeyer, J. S., Mahoney, J. P., & Muench, S. T. (2011). Use of the 1993 AASHTO Guide, MEPDG and Historical Performance to Update the WSDOT Pavement Design Catalog. Seattle, Washington: The University of Washington.spa
dc.relation.referencesLi, M., & Wang, H. (2017). Development of ANN-GA Program for Backcalculation of Pavement Moduli under FWD Testing with Viscoelastic and Nonlinear Parameters. International Journal of Pavement Engineering, 1-9.spa
dc.relation.referencesLi, Q., Xiao, D. X., Wang, K. C., Hall, K. D., & Qiu, Y. (2011). Mechanistic-Empirical Pavement Design Guide (MEPDG): A Bird's Eye Review. Journal of Modern Transportation, 19, 114-133.spa
dc.relation.referencesLi, T., & Chen, Y. (2018). Multiple Improvements to the Particle Swarm Optimization Algorithm. IOP Conference Series: Materials Science and Engineering, 435, pp. 1-10.spa
dc.relation.referencesLi, X., Li, X., Zhong, Y., & Wang, F. (2012). Modulus Back Analysis of Pavement Structure Based on PSO. Applied Mechanics and Materials, 178-181, 1222-1225.spa
dc.relation.referencesLiu, H., Pan, E., & Cai, Y. (2018). General surface loading over layered transversely isotropic pavements with imperfect interfaces. Advances in Engineering Software, 115, 268-282. doi:10.1016/j.advengsoft.2017.09.009spa
dc.relation.referencesLiu, P., Wang, D., & Oeser, M. (2015). Application of Semi-Analytical Finite Element Method Coupled with Infinite Element for Analysis of Asphalt Pavement Structural Response. Journal of Traffic and Transportation Engineering (English Version), 2(1), 45-48. doi:http://dx.doi.org/10.1016/j.jtte.2015.01.005spa
dc.relation.referencesLiu, W., & Scullion, T. (2011). Flexible Pavement Design Manual System FPS 21: User´s Manual. Texas Department of Transportation. College Station, TX: Texas Transportation Institute - The Texas A&M University System.spa
dc.relation.referencesLoulizi, A., Al-Qadi, I. L., & Elseifi, M. (2006). Difference between In Situ Flexible Pavement Measured and Calculated Stresses and Strains. Journal of Transportation Engineering, 132(7), 574-579.spa
dc.relation.referencesLu, Q., Ullidtz, P., Basheer, I., Ghuzlan, K., & Signore, J. M. (2009). CalBack: Enhancing Caltrans Mechanistic-Empirical Pavement Design Process with New Back-Calculation Software. Journal of Transportation Engineering, 135(7), 479-488.spa
dc.relation.referencesLui, M.-y., & Wang, S.-y. (2003). Genetic Optimization Method of Asphalt Pavement Based on Rutting and Cracking Control. Journal of Wuhan University of Technology, 18(1), 72-75.spa
dc.relation.referencesLuo, Z., Hu, B., & Pan, E. (2019). Robust design approach for flexible pavements to minimize the influence of material property uncertainty. Construction and Building Materials, 332-339.spa
dc.relation.referencesLuo, Z., Karki, A., Pan, E., Abbas, A. R., Arefin, M. S., & Hu, B. (2018). Effect of uncertain material property on system reliability in mechanistic-empirical pavement design. Construction and Building Materials, 172, 488-498.spa
dc.relation.referencesLytton, R. L. (1989). Backcalculation of Pavement Layer Properties. In A. J. Bush, & G. Y. Baladi (Ed.), Nondestructive Testing of Pavements and Backcalculation of Moduli ASTM STP1026 (pp. 7-38). Philadelphia: American Society for Testing and Materials.spa
dc.relation.referencesMaina, J. W., & Matsui, K. (2004). Developing software for elastic analysis of pavement structure responses. Transportation Research Records, 1896, 107-118.spa
dc.relation.referencesMaina, J. W., Ozawa, Y., & Matsui, K. (2012). Linear Elastic Analysis of Pavement Structure Under Non-circular Loading. Road Materials and Pavement Design, 13(3), 403-421. doi:10.1080/14680629.2012.705419spa
dc.relation.referencesMaji, A., & Das, A. (2008). Reliability considerations of bituminous pavement design by mechanistic-empirical approach. International Journal of Pavement Engineering, 9(1), 1-31.spa
dc.relation.referencesMaji, A., & Jha, M. K. (2007). Modeling Highway Infrastructure Maintenance Schedules with Budget Constraints. Transportation Research Record: Journal of the Transportation Research Board, 1991, 19-26.spa
dc.relation.referencesMallela, J., Glover, L. T., Liang, R. Y., & Chou, E. Y. (2009). Guidelines for Implementing NCHRP 1-37A M-E Design Procedures in Ohio. Volume 2 - Literature Review. Columbus, Ohio: Applied Research Associates, Inc. - Ohio Department of Transportation.spa
dc.relation.referencesMallick, R. B., & El-Korchi, T. (2009). Pavement engineering. Principles and practices (First ed.). Boca Raton, Florida, USA: CRC Press Taylor & Francis Group.spa
dc.relation.referencesMamlouk, M. S., Zaniewski, J. P., & He, W. (2000). Analysis and Design Optimization of Flexible Pavement. (A. S. Engineers, Ed.) ASCE Journal of Transportation Engineering, 126(2), 161.spa
dc.relation.referencesMarini, F., & Walczak, B. (2015). Particle Swarm Optimization (PSO). A tutorial. Chemometrics and Intelligent Laboratory Systems, 149, 153-165.spa
dc.relation.referencesMatin, A. G., Nezafat, R. V., & Golroo, A. (2017). A Comparative Study on Using Metaheuristic Algorithms for Road Maintenance Planning: Insights from Field Study in a Developing Country. Journal of Traffic and Transportation Engineering (English Edition), 4(5), 477-486.spa
dc.relation.referencesMendoza, C., & Caicedo, B. (2018). Elastoplastic Framework of Relationships between CBR and Young’s Modulus for Granular Material. Road Materials and Pavement Design, 19(8), 1796-1815. doi:10.1080/14680629.2017.1347517spa
dc.relation.referencesMeneses, S. (2013). Multi-Objective Decision-Aid Tool for Pavement Management. Ph.D. Thesis, University of Coimbra.spa
dc.relation.referencesMeneses, S., & Ferreira, A. (2012). Pavement Maintenance Programming Considering Two Objectives: Maintenance Costs And User Costs. International Journal of Pavement Engineering, 14(2), 206-221.spa
dc.relation.referencesMichelow, J. (1963). Analysis of stresses and displacements in N-layered elastic systems under a load uniformly distributed in a circular area. Richmond, CA, USA: California Research Corporation.spa
dc.relation.referencesMinisterio de Transporte - Oficina Asesora de Planeación. (2014). Transporte en Cifras - Estadísticas 2014. Bogotá: MinTransporte. Recuperado el 27 de Marzo de 2016, de https://www.mintransporte.gov.co/descargar.php?idFile=12621spa
dc.relation.referencesMonismith, C. L. (2004). Evolution of Long-Lasting Asphalt Pavement Design. Distinguished Lecture International Society for Asphalt Pavements. International Symposium on Design and Construction of Long-Lasting Asphalt Pavements (pp. 1-77). USA: Auburn University.spa
dc.relation.referencesMontoya-Rodriguez, C. (2015). Predicting Pavement Performance Under Traffic Loading Using Genetic Algorithms and Artificial Neural Networks to Obtain Resilient Modulus Values. Ph.D. Thesis, Ohio State University. Retrieved from https://etd.ohiolink.edu/spa
dc.relation.referencesMorcous, G., & Lounis, Z. (2005). Maintenance Optimization of Infrastructure Networks using Genetic Algorithms. Automation in Construction, 14, 129-142.spa
dc.relation.referencesNabhan, P. (2015). Calibration of the AASHTO MEPDG for Flexible Pavements to Fit Nevada's Conditions - M.Sc. Thesis. The University of Nevada. Reno, Nevada: The University of Nevada.spa
dc.relation.referencesNaseri, H., Shokoohi, M., Jahanbakhsh, H., Golroo, A., & Gandomi, A. H. (2021). Evolutionary and swarm intelligence algorithms on pavement maintenance and rehabilitation planning. International Journal of Pavement Engineering. doi:10.1080/10298436.2021.1969019spa
dc.relation.referencesNational Academies of Sciences, Engineering, and Medicine. (2012). Estimating the Effects of Pavement Condition on Vehicle Operating Costos. Washington, DC: The National Academies Press. doi:10.17226/22808spa
dc.relation.referencesNazzal, M. D., & Tatari, O. (2013). Evaluating the Use of Neural Networks and Genetic Algorithms for Prediction of Subgrade Resilient Modulus. International Journal of Pavement Engineering, 14(4), 364-373.spa
dc.relation.referencesNCHRP. (2004). Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures. National Cooperative Highway Research Program NCHRP Project 1-37A. Washington D.C.: National Research Council.spa
dc.relation.referencesNewcomb, D. E., Buncher, M., & Huddleston, B. W. (2001). Concepts of Perpetual Pavements. Transportation Research Board Circular No. 503, 4-11.spa
dc.relation.referencesNguyen, L. H. (2017, September). Research on the Correlation Between International Roughness Index (IRI) and Present Serviceability Index (PSI), Recommendations on Evaluation Rates in Vietnam's Conditions. International Journal of Engineering Research & Technology (IJERT), 6(09), 266-271. Retrieved from http://www.ijert.orgspa
dc.relation.referencesNik, A. A., Nejad, F. M., & Zakeri, H. (2016). Hybrid PSO and GA Approach for Optimizing Surveyed Asphalt Pavement Inspection Units in Massive Network. Automation in Construction, 71, 325-345.spa
dc.relation.referencesNilsson, R. N., Oost, I., & Hopman, P. C. (1996). Viscoelastic Analysis of Full-Scale Pavements: Validation of VEROAD. (T. R. Board, Ed.) Transportation Research Record 1539, 81-87.spa
dc.relation.referencesNovak, M., Birgisson, B., & Roque, R. (2003). Near-surface stress states in flexible pavements using measured radial tire contact stresses and ADINA. Computers and Structures, 81, 859-870.spa
dc.relation.referencesOppenlander, J. J., Heal, S. S., & Burns, L. D. (1971). Optimization of the Structural Design of Asphalt Pavements JHRP C-36-52I. Lafayette, Indiana: Purdue University.spa
dc.relation.referencesPanda, T. R., & Swamy, A. K. (2018). An Improved Artificial Bee Colony Algorithm for Pavement Resurfacing Problem. International Journal of Pavement Research and Technology, 11, 509-16.spa
dc.relation.referencesPapagiannakis, A. T., & Masad, E. A. (2008). Pavement design and materials (First ed.). Hoboken, NJ, USA: John Wiley & Sons.spa
dc.relation.referencesPark, S.-W., Park, H. M., & Hwang, J.-J. (2010). Application of Genetic Algorithm and Finite Element Method for Backcalculating Layer Moduli of Flexible Pavements. KSCE Journal of Civil Engineering, 14(2), 183-190.spa
dc.relation.referencesPeddinti, P. T., Basha, B. M., & Saride, S. (2020). System Reliability Framework for Design of Flexible Pavements. Journal of Transportation Engineering. Part B: Pavements, 146(3).spa
dc.relation.referencesPekcan, O., Tutumluer, E., & Ghaboussi, J. (2010). Soft Computing Methodology to Determine Pavement Thickness from Falling Weight Deflectometer Testing. GeoFlorida 2010: Advances in Analysis, Modeling & Design (GSP 199) (pp. 2621-2630). West Palm Beach, Florida: American Society of Civil Engineers.spa
dc.relation.referencesPereira, P., & Pais, J. (2017). Main flexible pavement and mix design methods in Europe and challenges for the development of a European method. Journal of Traffic and Transportation Engineering, 4, 316-346.spa
dc.relation.referencesPeutz, M., Van Kempen, H., & Jones, A. (1968). Layered Systems Under Normal Surface Loads. Highway Research Record, 228, 33-45.spa
dc.relation.referencesPierce, L. M., & McGovern, G. (2014). Implementation of the AASHTO Mechanistic-Empirical Pavement Design Guide and Software - NCHRP Synthesis 457. Washington, D.C.: Transportation Research Board.spa
dc.relation.referencesPijarski, P., & Kacejko, P. (2019). A New Metaheuristic Optimization Method: The Algorithm of the Innovative Gunner (AIG). Engineering Optimization, 1-20. doi:10.1080/0305215X.2019.1565282spa
dc.relation.referencesPilson, C., Hudson, W. R., & Anderson, V. (1999). Multiobjective Optimization in Pavement Management by Using Genetic Algorithms and Efficient Surfaces. Transportation Research Record: Journal of the Transportation Research Board, 1655, 42-48.spa
dc.relation.referencesPorter, O. J. (1942). Foundations for Flexible Pavements. Proceedings of the Highway Research Board (pp. 10-36). Washington, D.C.: HRB.spa
dc.relation.referencesPoulos, H. G., & Davis, E. H. (1974). Elastic Solutions for Soil and Rock Mechanics. New York, USA: John Wiley & Sons, Inc. Retrieved 03 24, 2016, from http://research.engr.oregonstate.edu/usucger/PandD/PandD.htmspa
dc.relation.referencesPowell, M. J. (2004). The NEWUOA Software for Unconstrained Optimization Without Derivatives. The 40th Workshop on Large Scale Nonlinear Optimization. Erice, Italy.spa
dc.relation.referencesPryke, A., Evdorides, H., & Ermaileh, R. A. (2006). Optimization of Pavement Design Using a Genetic Algorithm. 2006 IEEE Congress on Evolutionary Computation (pp. 1095-1098). Vancouver: IEEE.spa
dc.relation.referencesQian, W.-d. (2010). Road Pavement Performance Evaluation Model Based on Hybrid Genetic Algorithm Neural Network. 2010 Second International Conference on Computational Intelligence and Natural Computing CINC (pp. 209-212). IEEE.spa
dc.relation.referencesQuijano-Bernal, C. A. (2016). Aplicación de Redes Neuronales en el Cálculo Inverso de Pavimentos Flexibles - Trabajo de grado en modalidad de monografía. Ingeniería Civil. Manizales: Universidad Nacional de Colombia.spa
dc.relation.referencesRabinovitz, P. (1990). Numerical integration based on approximating splines. (E. S. B.V., Ed.) Journal of Computational and Applied Mathematics, 33, 73-83.spa
dc.relation.referencesRajbongshi, P. (2014). Reliability Based Cost Effective Design of Asphalt Pavements Considering Fatigue and Rutting. International Journal of Pavement Research and Technology, 7(2), 153-158.spa
dc.relation.referencesRajbongshi, P., & Das, A. (2008). Optimal Asphalt Pavement Design Considering Cost and Reliability. ASCE Journal of Transportation Engineering, 134(6), 255-261.spa
dc.relation.referencesRakesh, N., Jain, A. K., Reddy, M. A., & Reddy, K. S. (2006). Artificial Neural Networks - Genetic Algorithm Based Model for Backcalculation of Pavement Layer Moduli. International Journal of Pavement Engineering, 7(3), 221-230.spa
dc.relation.referencesReddy, M. A., Reddy, K. S., & Pandey, B. B. (2004). Selection of Genetic Algorithm Parameters for Backcalculation of Pavement Moduli. The International Journal of Pavement Engineering, 5(2), 81-90.spa
dc.relation.referencesReyes Lizcano, F., Caicedo, B., & Yamin, L. (1997). Manual de diseño de pavimentos para Bogotá D.C. Bogotá D.C.: Instituto de Desarrollo Urbano - IDU - Universidad de Los Andes.spa
dc.relation.referencesRifai, A. I., Hadiwardoyo, S. P., Comes Correia, A., & Pereira, P. (2016). Genetic Algorithm Applied for Optimization of Pavement Maintenance under Overload Traffic: Case Study Indonesia National Highway. Applied Mechanics and Materials, 369-378.spa
dc.relation.referencesRojas-Pérez, F., Aguiar-Moya, J.-P., & Loría-Salazar, L.-G. (2015). PITRAPAVE - Software de multicapa elástica. (U. d.-L. (LANAMME), Ed.) San José de Costa Rica, Costa Rica: Laboratorio Nacional de Materiales y Modelos Estructurales.spa
dc.relation.referencesRomanoschi, S., Lewis, P., Gedafa, D., & Hossain, M. (2014). Verification of Mechanistic-Empirical Design Models for Flexible Pavements through Accelerated Pavement Testing - Report FHWA-KS-14-02. Topeka, Kansas: Kansas State University Transportation Center.spa
dc.relation.referencesRouphail, N. M. (1985). Minimum-Cost Design of Flexible Pavements. Journal of Transportation Engineering, 111(3), 196-207.spa
dc.relation.referencesSalari, E., & Yu, X. (2011). Pavement Distress Detection and Classification Using a Genetic Algorithm. IEEE Applied Imagery Pattern Recognition Workshop 41PR (pp. 1-5). IEEE.spa
dc.relation.referencesSánchez-Silva, M., Arroyo, O., Junca, M., Caro, S., & Caicedo, B. (2005). Reliability-Based Design Optimization of Asphalt Pavements. The International Journal of Pavement Engineering, 6(4), 281-294.spa
dc.relation.referencesSantos, J., & Ferreira, A. (2012a). Pavement Design Optimization Considering Costs and Preventive Interventions. Journal of Transportation Engineering, 138(7), 911 - 923.spa
dc.relation.referencesSantos, J., & Ferreira, A. (2012b). Pavement design optimization considering costs and M&R interventions. Procedia - Social and Behavioral Sciences, 53, 1184 - 1193.spa
dc.relation.referencesSantos, J., & Ferreira, A. (2013). Life-Cycle Cost Analysis System for Pavement Management at Project Level. International Journal of Pavement Engineering, 14(1), 71-84.spa
dc.relation.referencesSantos, J., Fereira, A., & Flintsch, G. (2017). An Adaptive Hybrid Genetic Algorithm for Pavement Management. International Journal of Pavement Engineering, 20(3), 266-286.spa
dc.relation.referencesSaride, S., Peddinti, P. R., & Basha, M. B. (2019). Reliability Perspective on Optimum Design of Flexible Pavements for Fatigue and Rutting Performance. Journal of Transportation Engineering, Part B: Pavements, 145(2).spa
dc.relation.referencesSawyers, M. W., Gillespie, T. D., & Paterson, W. D. (1986). Guidelines for conducting and calibrating road roughness measurements (No. Technical Paper 46). Washington, DC: The World Bank.spa
dc.relation.referencesSchwartz, C. W., & Carvalho, R. L. (2007). Implementation of the NCHRP 1-37A Design Guide. Final Report. Volume 2: Evaluation of Mechanistic-Empirical Design Procedure (Vol. 2). College Park, Maryland, USA: University of Maryland.spa
dc.relation.referencesSchwartz, C. W., Kim, S. H., Ceylan, H., & Gopalakrishnan, K. (2011). Sensitivity Evaluation of MEPDG Performance Prediction. College Park, Maryland: University of Maryland - Iowa State University.spa
dc.relation.referencesScimemi, G. F., Turetta, T., & Celauro, C. (2016). Backcalculation of airport pavement moduli and thickness using the Lévy Ant Colony Optimization Algorithm. Construction and Building Materials, 288-295.spa
dc.relation.referencesSenseney, C. T., Krahenbuhl, R. A., & Mooney, M. A. (2013). Genetic Algorithm to Optimize Layer Parameters in Light Weight Deflectometer Backcalculation. International Journal of Geomechanics, 13(4), 473-476.spa
dc.relation.referencesShahin, M. Y. (2006). Pavement Management for Airports, Roads, and Parking Lots (Second ed.). Springer.spa
dc.relation.referencesShahnazari, H., Tutunchian, M. A., Mashayekhi, M., & Amini, A. A. (2012). Application of Soft Computing for Prediction of Pavement Condition Index. Journal of Transportation Engineering, 138(12), 1495-1506.spa
dc.relation.referencesSharma, L. K., Singh, R., Umrao, R. K., Sahrma, K., & Singh, T. N. (2017). Evaluating the modulus of elasticity of soil using soft computing system. Engineering with Computers, 33, 497-507. doi:10.1007/s00366-016-0486-6spa
dc.relation.referencesShekharan, A. R. (2000). Solution of Pavement Deterioration Equations by Genetic Algorithms. Transportation Research Record: Journal of the Transportation Research Board, 1699, 101-106.spa
dc.relation.referencesShell Oil. (1978). Shell Pavement Design Manual: Asphalt Pavements and Overlays for Road Traffic. London, UK: Shell International Petroleum Company, Ltd.spa
dc.relation.referencesShen, Y., Bu, Y., & Yuan, M. (2009). A Novel Chaos Particle Swarm Optimization (PSO) and Its Application in Pavement Maintenance Decision. ICIEA 2019 (pp. 3521-3526). IEEE.spa
dc.relation.referencesShi, Y. E., & Berhart, R. C. (1998). A Modified Particle Swarm Optimizer. Proceedings of the IEEE Congress on Evolutionary Computation. 6, pp. 69-73. IEEE.spa
dc.relation.referencesSidess, A., & Uzan, J. (2009). A design method of perpetual flexible pavement in Israel. International Journal of Pavement Engineering, 241-249.spa
dc.relation.referencesSouthgate, H. F., Deen, R. C., Cain, D., & Mayes, J. G. (1987). Modifications to CHEVRON N-Layer program Research Report UKTRP-87-28. Lexington, KY: Kentucky Transportation Center Research.spa
dc.relation.referencesStrickland, D. (2000). Shell Pavement Design Software for Windows. London: Shell International Petroleum Company.spa
dc.relation.referencesSufian, A. A. (2016). Local Calibration of the Mechanistic Empirical Pavement Design Guide for Kansas - M.Sc. Thesis. Kansas State University. Manhattan, Kansas: Kansas State University.spa
dc.relation.referencesSuh, Y., Mun, S., & Yeo, I. (2010). Fatigue Life Prediction of Asphalt Concrete Pavement Using a Harmony Search Algorithm. KSCE Journal of Civil Engineering, 14(5), 725-730.spa
dc.relation.referencesSundin, S., & Braban-Ledoux, C. (2001). Artificial Intelligence-Based Decision Support Technologies in Pavement Management. Computer-Aided Civil And Infrastructure Engineering, 16, 143-157.spa
dc.relation.referencesTack, J. N., & Chou, E. Y. (2002). Multiyear Pavement Repair Scheduling Optimization by Preconstrained Genetic Algorithm. Transportation Research Record: Journal of the Transportation Research Board, 1816, 3-9.spa
dc.relation.referencesTaha, M. A., & Hanna, A. S. (1995). Evolutionary Neural Network Model for the Selection of Pavement Maintenance Strategy. Transportation Research Record: Journal of the Transportation Research Board, 1497, 70-76.spa
dc.relation.referencesTao, X., Huang, J., & Cai, Y. (2013). Inverse Analysis for Inhomogeneous Dielectric Coefficient of Pavement Material Based on Genetic Algorithm. Applied Mechanics and Materials, 438-439, 430-435.spa
dc.relation.referencesTarefder, R. A., & Bateman, D. (2012). Design of Optimal Perpetual Pavement Structure. Journal of Transportation Engineering, 138(2), 157-175.spa
dc.relation.referencesTarefder, R., & Rodriguez-Ruiz, J. I. (2013). Local Calibration of MEPDG for Flexible Pavements in New Mexico. Journal of Transportation Engineering, 139(10), 981-991.spa
dc.relation.referencesTayebi, N. R. (2010). Analysis of Pavement Management Activities Programming by Particle Swarm Optimization. Proceedings of the International Conference on Advances in Electrical & Electronics (pp. 149-154). ACEEE.spa
dc.relation.referencesTayebi, N. R., Nejad, F. M., & Mola, M. (2014). Comparison between GA and PSO in Analyzing Pavement Management Activities. Journal of Transportation Engineering, 140(1), 99-104.spa
dc.relation.referencesTeodorovic, D. (2008). Swarm Intelligence Systems for Transportation Engineering: Principles and Applications. Transportation Research Part C, 16, 651-667.spa
dc.relation.referencesTerzi, S. (2005). Modeling the Deflection Basin of Flexible Highway Pavements by Gene Expression Programming. Journal of Applied Sciences, 5(2), 309-314.spa
dc.relation.referencesTerzi, S., & Serin, S. (2014). Planning Maintenance Works on Pavements Through Ant Colony Optimization. Neural Computing & Applications, 25(143), 143-153.spa
dc.relation.referencesTerzi, S., Saltan, M., & Yildirim, T. (2003). Optimization of the Deflection Basin by Genetic Algorithm and Neural Network Approach. In O. Kaynak (Ed.), ICANN/ICONIP 2003 (pp. 662-669). Springer-Verlag Berlin Heidelberg.spa
dc.relation.referencesThe South African National Roads Agency. (2014). South African Pavement Engineering Manual - Introduction. Johannesburg: The South African National Roads Agency.spa
dc.relation.referencesThom, N. (2008). Principles of pavement engineering. London, UK: Thomas Telford Publishing Ltd.spa
dc.relation.referencesThompson, M. R., & Barenberg, E. J. (1989). Calibrated Mechanistic Structural Analysis Procedures for Pavements: Phase I—Final Report, NCHRP Project 1-26. Washington, D.C.: Transportation Research Board, National Research Council.spa
dc.relation.referencesThompson, M. R., & Elliot, R. P. (1988). “ILLI-PAVE Based Response Algorithms for Design of Conventional Flexible Pavements. Transportation Research Record 1207, 145-168.spa
dc.relation.referencesTimm, D. H., Newcomb, D. E., & Galambos, T. V. (2000). Incorporation of Reliability into Mechanistic-Empirical Pavement Design. Transportation Research Record: Journal of the Transportation Research Board, 1730, 73-80.spa
dc.relation.referencesTimm, D. H., Robbins, M. M., Tran, N., & Rodezno, C. (2014). Flexible Pavement Design - State of the Practice NCAT Report 14-04. Auburn, AL: National Center for Asphalt Technology - NCAT.spa
dc.relation.referencesTimoshenko, S., & Goodier, J. N. (1951). Theory of Elasticity. New York, USA: McGraw-Hill Book Company Inc.spa
dc.relation.referencesToklu, Y. C. (2014). An Overview of Metaheuristic Algorithms. In Y. C. Toklu, & G. Bekdas (Ed.), Metaheuristics and Engineering Proceedings of the 15th EU/ME Workshop (pp. 13-16). Istambul, Turkey: Bilecik Seyh Edebali University.spa
dc.relation.referencesTran, N., Robbins, M. M., Rodezno, C., & Timm, D. H. (2017). Pavement ME Design - Impact of Local Calibration, Foundation Support, and Design and Reliability Thresholds - NCAT Report 17-08. Auburn University. Auburn, Alabama: National Center for Asphalt Technology.spa
dc.relation.referencesTransport Research Laboratory. (1993). Overseas Road Note 31 A Guide to the Structural Design of Bitumen-Surfaced Roads in Tropical and Sub-Tropical Countries. Crowthorne, Berkshire: Transport Research Laboratory.spa
dc.relation.referencesTransport Research Laboratory. (2002). Overseas Road Note 19 A guide to the design of hot mix asphalt in tropical and sub-tropical countries. London, UK: TRL Limited.spa
dc.relation.referencesTrejos Castillo, C., Leiva Padilla, P., & Loría Salazar, G. (2014). Interfaz Gráfica para Diseño Mecanístico-Empírico de Pavimentos en Costa Rica CR-ME Versión 1 Guía del Usuario. San José: Laboratorio Nacional de Materiales y Modelos Estructurales - Universidad de Costa Rica.spa
dc.relation.referencesTsai, B.-W., Harvey, J. T., & Monismith, C. L. (2009). Case Studies of Asphalt Pavement Analysis/Design with Application of the Genetic Algorithm. (K. Gopalakrishnan, & N. O. Attoh-Okine, Eds.) Studies in Computational Intelligence 259. Intelligent and Soft Computing in Infrastructure Systems Engineering. Recent Advances, 205-238. doi:10.1007/978-3-642-04586-8spa
dc.relation.referencesTsai, B.-W., Kannekanti, V. N., & Harvey, J. T. (2004). Transportation Research Record: Journal of the Transportation Research Board, 1891, 112-120.spa
dc.relation.referencesTsunokawa, K., Van Hiep, D., & Ul-Islam, R. (2006). True Optimization of Pavement Maintenance Options with What-If Models. Computer-Aided Civil and Infrastructure Engineering, 21, 193-204.spa
dc.relation.referencesTutumluer, E., & Barksdale, R. D. (1995). Behaviour of pavements with granular bases - prediction and performance. Unbound aggregates in roads, 173-183.spa
dc.relation.referencesTutumluer, E., & Sarker, P. (2015). Development of Improved Pavement Rehabilitation Procedures Based on FWD Backcalculation - NEXTRANS Project No. 094/Y04. Urbana-Champaign, Illinois: NEXTRANS USDOT V Regional University Transportation Center.spa
dc.relation.referencesUllidtz, P. (1987). Pavement analysis. Amsterdam: Elsevier.spa
dc.relation.referencesUllidtz, P., Harvey, J., Basheer, I., Jones, D., Wu, R., Jeremy, L., & Lu, Q. (2010). CalME, a Mechanistic-Empirical Program to Analyze and Design Flexible Pavement Rehabilitation. Transportation Research Record: Journal of the Transportation Research Board, 2153, 143-152.spa
dc.relation.referencesUniversidad Nacional de Colombia. (2013). Cartilla guía de diseño de pavimentos con bajos volúmenes de tránsito y vías locales para la ciudad de Bogotá D.C. Bogotá: Universidad Nacional de Colombia - Instituto de Desarrollo Urbano - Banco de Desarrollo para América Latina.spa
dc.relation.referencesUnnikrishnan, A., Valsaraj, V., Damnjanovic, I., & Waller, S. T. (2009). Design and Management Strategies for Mixed Public Private Transportation Networks: A Meta-Heuristic Approach. Computer-Aided Civil and Infrastructure Engineering, 24, 266-279.spa
dc.relation.referencesUzan, J. (1994). Advanced back-calculation techniques. Second International Symposium on NDT of Pavements and Backcalculation (pp. 3-37). Philadelphia, Pa, USA: ASTM Special Technical Publications.spa
dc.relation.referencesVan Cauwelaert, F. J., & Lequeux, D. (1986). Computer Programs for the Determination of Stresses and Displacements in Four Layered Structures. Waterways Experiment Station. Vicksburg, Miss.: U.S. Army Corps of Engineers.spa
dc.relation.referencesVan den Bergh, F., & Engelbrecht, A. (2002). A New Locally Convergent Particle Swarm Optimizer. International Conference on Systems, Man and Cybernetics. 3. IEEE.spa
dc.relation.referencesVan Hiep, D. (2009). Optimization of Pavement Designs and / or Maintenance Strategies Using Gradient Search with Option Evaluation Systems. Ph.D. Thesis, Saitama University.spa
dc.relation.referencesVarma, S., Kutay, M. E., & Levenberg, E. (2013). Viscoelastic Genetic Algorithm for Inverse Analysis of Asphalt Layer Properties from Falling Weight Deflections. Transportation Research Record: Journal of the Transportation Research Board, 2369, 38-46.spa
dc.relation.referencesVásquez Varela, L. R. (14 de Mayo de 2015). Aplicación de la Mecánica de Sólidos en Ingeniería de Pavimentos. Recuperado el 24 de Marzo de 2016, de Ingepav - Ingeniería de pavimentos por Luis Ricardo Vásquez Varela: https://sites.google.com/site/ingepav/diseno-y-analisis/mecanicadesolidoisaplicadaapavimentosspa
dc.relation.referencesVásquez-Varela, L. R., & García-Orozco, F. J. (2019). UNLEA A Multilayer Elastic Program Script in Scilab. International Airfield and Highway Pavements Conference 2019. Chicago, IL: American Society of Civil Engineers. doi:https://doi.org/10.1061/9780784482452.010spa
dc.relation.referencesVásquez-Varela, L. R., & García-Orozco, F. J. (2020). An overview of asphalt pavement design for streets and roads. Revista Facultad De Ingeniería Universidad De Antioquia(98), 10-26. doi:https://doi.org/10.17533/udea.redin.20200367spa
dc.relation.referencesVásquez-Varela, L. R., & García-Orozco, F. J. (2021). Applied Metaheuristic Optimization in Asphalt Pavement Management. Ciencia e Ingeniería Neogranadina, 75-92. doi:https://doi.org/10.18359/rcin.4371spa
dc.relation.referencesVelasquez, R., Hoegh, K., Yut, I., Funk, N., Cochran, G., Marasteanu, M., & Khazanovich, L. (2009). Implementation of the MEPDG for New and Rehabilitated Pavement Structures for Design of Concrete and Asphalt Pavements in Minnesota. Saint Paul, Minnesota: Minnesota Department of Transportation.spa
dc.relation.referencesVerstraeten, J., Veverka, V., & Francken, L. (1982). Rational and Practical Designs of Asphalt Pavements to Avoid Cracking and Rutting. Proceedings Fifth International Conference on the Structural Design of Asphalt Pavements (pp. 42-58). University of Michigan and Delft University of Technology.spa
dc.relation.referencesVon Quintus, H. L., & Simpson, A. L. (2002). Back-Calculation of Layer Parameters for LTPP Test Sections, Volume II: Layered Elastic Analysis for Flexible and Rigid Pavements - FHWA-RD-01-113. McLean, Virginia: Federal Highway Administration.spa
dc.relation.referencesVon Quintus, H. L., Mallela, J., Bonaquist, R., Schwartz, C. W., & Carvalho, R. L. (2012). Calibration of Rutting Models for Structural and Mix Design - NCHRP Report 719. Washington, D.C.: Transportation Research Board.spa
dc.relation.referencesWalker, R. N., Patterson, W. D., Freeme, C. R., & Marias, C. P. (1977). The South African Mechanistic Pavement Design Procedure. Proceedings, Fourth International Conference on the Structural Design of Asphalt Pavements. 2. The University of Michigan.spa
dc.relation.referencesWalls, I. J., & Smith, M. R. (1998). Life-Cycle Cost Analysis in Pavement Design - Interim Technical Bulletin Report No. FHWA-SA-98-079. Washington D.C., USA: Federal Highway Administration.spa
dc.relation.referencesWang, D., Roesler, J. R., & Guo, D.-Z. (2011). Innovative Algorithm to Solve Axisymmetric Displacement and Stress Fields in Multilayered Pavement Systems. ASCE Journal of Transportation Engineering, 137(4), 287-295. doi:10.1061/(ASCE)TE.1943-5436.0000208spa
dc.relation.referencesWang, K. C., Nguyen, V., & Zaniewski, J. P. (2007). Genetic Algorithms-Based Network Optimization System with Multiple Objectives. Transportation Research Record: Journal of the Transportation Research Board, 2016, 85-95.spa
dc.relation.referencesWardle, L. J. (1977). Program CIRCLY. A Computer Program for the Analysis of Multiple Complex Loads on Layered Anisotropic Media. Victoria, Australia: Division of Applied Geomechanics and Commonwealth Scientific and Industrial Research Organisation.spa
dc.relation.referencesWarren, H., & Dieckmann, W. L. (1963). Numerical Computation of Stresses and Strains in a Multiple-Layered Asphalt Pavement System. Richmond, California: California Research Corporation.spa
dc.relation.referencesWatanatada, T., Harral, C. G., Paterson, W. D., Dhareshwar, A. M., Bhandari, A., & Tsunokawa, K. (1987). The Highway Design And Maintenance Standards Model Volume 1: Description of the HDM-III Model.The Highway Design and Maintenance Standards Series. The World Bank. Baltimore, USA: Johns Hopkins Press. Retrieved from http://www.worldbank.org/transport/roads/rd_tools/hdm-iii%20_vol-1.pdfspa
dc.relation.referencesWhiteoak, D. (1991). The Shell Bitumen Handbook. Surrey, UK: Shell Bitumen UK.spa
dc.relation.referencesWilliams, R. C., & Shaidur, R. (2013). Mechanistic-Empirical Pavement Design Guide Calibration for Pavement Rehabilitation - Final report SPR 718. Salem, Oregon: Oregon Department of Transportation - Federal Highway Administration.spa
dc.relation.referencesWu, Z., Flintsch, G., Ferreira, A., & de Picado-Santos, L. (2012). Framework for Multiobjective Optimization of Physical Highway Assets Investments. Journal of Transportation Engineering, 138(12), 1411-1421.spa
dc.relation.referencesXinchao, Z. (2010). A Perturbed Particle Swarm Algorithm for Numerical Optimization. Applied Soft Computing, 10, 119-124.spa
dc.relation.referencesYang, C., Remenyte-Prescott, R., & Andrews, J. D. (2015). Pavement Maintenance Scheduling Using Genetic Algorithms. International Journal of Performability Engineering, 11(2), 135-152.spa
dc.relation.referencesYang, N. C. (1972). Design of functional pavements. (W. G. Salo Jr., J. Ely, & D. A. Douglas, Eds.) New York, NY, USA: McGraw-Hill.spa
dc.relation.referencesYang, X. -S. (2011). Metaheuristic Optimization: Algorithm Analysis and Open Problems. National Physics Laboratory.spa
dc.relation.referencesYang, X. S. (2013). Optimization and Metaheuristic Algorithms in Engineering. Metaheuristics in Water, Geotechnical and Transport Engineering, 1-23.spa
dc.relation.referencesYang, X.-S., Koziel, S., & Leifsson, L. (2014). Computational Optimization, Modelling and Simulation: Past, Present and Future. Procedia Computer Science ICCS 2014 14th International Conference on Computational Science. Volume 29, pp. 754-758. Cairns, Australia: Elsevier. doi:10.1016/j.procs.2014.05.067spa
dc.relation.referencesYepes, V., Torres-Machi, C., Chamorro, A., & Pellicer, E. (2016). Optimal Pavement Maintenance Programs based on a Hybrid Greedy Randomized Adaptative Search Procedure Algorithm. Journal of Civil Engineering and Management, 22(4), 540-550.spa
dc.relation.referencesYoder, E. J., & Witczak, M. W. (1975). Principles of Pavement Design (Second ed.). New York, USA: John Wiley & Sons, Inc.spa
dc.relation.referencesYoshimura, J., Ushio, S., & Sugawara, T. (1972). Stresses in Multi Layered Systems. Memoirs of the Faculty of Engineering, Hokkaido University, 03, 75-89.spa
dc.relation.referencesZaabar, I., Chatti, K., Suk-Lee, H., & Lajnef, N. (2014). Backcalculation of Asphalt Concrete Modulus Master Curve from Field-Measured Falling Weight Deflectometer Data - Using a New Time Domain VIscoelastic Dynamic Solution and Genetic Algorithm. Transportation Research Record: Journal of the Transportation Research Board, 2457, 80-92.spa
dc.relation.referencesZhao, Y., Liu, W., & Tan, Y. (2012). Analysis of Critical Structure Responses for Flexible Pavements in NCHRP 1-37A Mechanistic-Empirical Pavement Design Guide. Journal of Transportation Engineering, 138(8), 983-990.spa
dc.relation.referencesZhao, Y., Zhou, C., Zeng, W., & Ni, Y. (2015). Accurate determination of near-surface responses of asphalt pavements. Road Materials and Pavement Design, 16(1), 186-199. doi:10.1080/14680629.2014.979221spa
dc.relation.referencesZiari, H., & Khabiri, M. M. (2007). Interface condition influence on prediction of flexible pavement life. Journal of Civil Engineering and Management, 71-76.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-CompartirIgual 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/spa
dc.subject.ddc620 - Ingeniería y operaciones afines::625 - Ingeniería de ferrocarriles y de carreteraspa
dc.subject.lembPavimento -- Diseño y construcciónspa
dc.subject.proposalPavimento asfálticospa
dc.subject.proposalDiseñospa
dc.subject.proposalCálculo inversospa
dc.subject.proposalMetaheurísticaspa
dc.subject.proposalAsphalt pavementeng
dc.subject.proposalDesigneng
dc.subject.proposalBackcalculationeng
dc.subject.proposalMetaheuristiceng
dc.titleOptimization of the structural design of asphalt pavements for streets and highwayseng
dc.title.translatedOptimización del diseño estructural de pavimentos asfálticos para calles y carreterasspa
dc.typeTrabajo de grado - Doctoradospa
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dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentMaestrosspa
dcterms.audience.professionaldevelopmentPúblico generalspa
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