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How to cite this paper
APA: Chávez, J., Escobar, J & Echeverri, M. (2016). A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls. International Journal of Industrial Engineering Computations, 7(1), 35-48.
Chicago/Turabian: Chávez, J., Escobar, J & Echeverri, M. 2016. "A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls." International Journal of Industrial Engineering Computations 7, no. 1 (2016): 35-48.
AMA: Chávez, J., Escobar, J & Echeverri, M. A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls. International Journal of Industrial Engineering Computations. 2016;7(1):35-48.
References
Anbuudayasankar, S. P., Ganesh, K., Koh, S. L., & Ducq, Y. (2012). Modified savings heuristics and genetic algorithm for bi-objective vehicle routing problem with forced backhauls. Expert Systems with Applications, 39(3), 2296-2305.
Bekta?, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Bola?os, R., Echeverry, M., & Escobar, J. (2015). A multiobjective non-dominated sorting genetic algorithm (NSGA-II) for the Multiple Traveling Salesman Problem. Decision Science Letters, 4(4), 559-568.
Chunyu, R., Zhendong, S., & Xiaobo, W. (2009, June). Study on single and mixed fleet strategy for multi-depot vehicle routing problem with backhauls. In Computational Intelligence and Natural Computing, 2009. CINC & apos; 09. International Conference on (Vol. 1, pp. 425-428). IEEE.
Chunyu, R., & Xiaobo, W. (2009, October). Study on hybrid genetic algorithm for multi-type vehicles and multi-depot vehicle routing problem with backhauls. In Intelligent Computation Technology and Automation, 2009. ICICTA & apos; 09. Second International Conference on (Vol. 1, pp. 197-200). IEEE.
Demir, E., Bekta?, T., & Laporte, G. (2014). The bi-objective pollution-routing problem. European Journal of Operational Research, 232(3), 464-478.
Doerner, K., Gutjahr, W. J., Hartl, R. F., Strauss, C., & Stummer, C. (2004). Pareto ant colony optimization: A metaheuristic approach to multiobjective portfolio selection. Annals of Operations Research, 131(1-4), 79-99.
Escobar, J. W., Linfati, R., & Toth, P. (2013). A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Computers & Operations Research, 40(1), 70-79.
Escobar, J. W., Linfati, R., Toth, P., & Baldoquin, M. G. (2014a). A hybrid granular tabu search algorithm for the multi-depot vehicle routing problem. Journal of Heuristics, 20(5), 483-509.
Escobar, J. W., Linfati, R., Baldoquin, M. G., & Toth, P. (2014b). A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem. Transportation Research Part B: Methodological, 67, 344-356.
Escobar, J. W., Linfati, R., & Adarme-Jaimes, W. (2015). A hybrid metaheuristic algorithm for the capacitated location routing problem. Dyna, 82(189), 243-251.
Garc?a-N?jera, A., Bullinaria, J. A., & Gutiérrez-Andrade, M. A. (2015). An evolutionary approach for multi-objective vehicle routing problems with backhauls. Computers & Industrial Engineering, 81, 90-108.
Gutjahr, W. J. (2002). ACO algorithms with guaranteed convergence to the optimal solution. Information Processing Letters, 82(3), 145-153.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2008). Multi-objective vehicle routing problems. European Journal of Operational Research, 189(2), 293-309.
Lau, H. C., Chan, T. M., Tsui, W. T., Chan, F. T., Ho, G. T., & Choy, K. L. (2009). A fuzzy guided multi-objective evolutionary algorithm model for solving transportation problem. Expert Systems with Applications, 36(4), 8255-8268.
Liu, C. M., Chang, T. C., & Huang, L. F. (2006). Multi-objective heuristics for the vehicle routing problem. International Journal of Operations Research, 3(3), 173-181.
Min, H., Current, J., & Schilling, D. (1992). The multiple depot vehicle routing problem with backhauling. Journal of Business Logistics, 13(1), 259.
Mohammadi, M., Tavakkoli-Moghaddam, R., & Rostami, R. (2011). A multi-objective imperialist competitive algorithm for a capacitated hub covering location problem. International Journal of Industrial Engineering Computations, 2(3), 671-688.
Mortezaei, M., & JabalAmeli, M. (2011). A hybrid model for multi-objective capacitated facility location network design problem. International Journal of Industrial Engineering Computations, 2(3), 509-524.
Nezhad, A., Roghanian, E., & Azadi, Z. (2013). A fuzzy goal programming approach to solve multi-objective supply chain network design problems. International Journal of Industrial Engineering Computations, 4(3), 315-324.
Rao, R., & Patel, V. (2014). A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems. International Journal of Industrial Engineering Computations, 5(1), 1-22.
Ropke, S., & Pisinger, D. (2006). A unified heuristic for a large class of vehicle routing problems with backhauls. European Journal of Operational Research, 171(3), 750-775.
Salhi, S., & Nagy, G. (1999). A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling. Journal of the Operational Research Society, 50(10), 1034-1042.
Wade, A., & Salhi, S. (2001, July). An ant system algorithm for the vehicle routing problem with backhauls. In MIC?2001––4th Metaheuristic International Conference.
Wade, A., & Salhi, S. (2004). An ant system algorithm for the mixed vehicle routing problem with backhauls. In Metaheuristics: computer decision-making (pp. 699-719). Springer US.
Yalc?n, G. D., & Erginel, N. (2015). Fuzzy multi-objective programming algorithm for vehicle routing problems with backhauls. Expert Systems with Applications, 42(13), 5632-5644.
Yazdian, S., & Shahanaghi, K. (2011). A multi-objective possibilistic programming approach for locating distribution centers and allocating customers demands in supply chains. International Journal of Industrial Engineering Computations, 2(1), 193-202.
Zhou, A., Qu, B. Y., Li, H., Zhao, S. Z., Suganthan, P. N., & Zhang, Q. (2011). Multiobjective evolutionary algorithms: A survey of the state of the art. Swarm and Evolutionary Computation, 1(1), 32-49.
Bekta?, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Bola?os, R., Echeverry, M., & Escobar, J. (2015). A multiobjective non-dominated sorting genetic algorithm (NSGA-II) for the Multiple Traveling Salesman Problem. Decision Science Letters, 4(4), 559-568.
Chunyu, R., Zhendong, S., & Xiaobo, W. (2009, June). Study on single and mixed fleet strategy for multi-depot vehicle routing problem with backhauls. In Computational Intelligence and Natural Computing, 2009. CINC & apos; 09. International Conference on (Vol. 1, pp. 425-428). IEEE.
Chunyu, R., & Xiaobo, W. (2009, October). Study on hybrid genetic algorithm for multi-type vehicles and multi-depot vehicle routing problem with backhauls. In Intelligent Computation Technology and Automation, 2009. ICICTA & apos; 09. Second International Conference on (Vol. 1, pp. 197-200). IEEE.
Demir, E., Bekta?, T., & Laporte, G. (2014). The bi-objective pollution-routing problem. European Journal of Operational Research, 232(3), 464-478.
Doerner, K., Gutjahr, W. J., Hartl, R. F., Strauss, C., & Stummer, C. (2004). Pareto ant colony optimization: A metaheuristic approach to multiobjective portfolio selection. Annals of Operations Research, 131(1-4), 79-99.
Escobar, J. W., Linfati, R., & Toth, P. (2013). A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Computers & Operations Research, 40(1), 70-79.
Escobar, J. W., Linfati, R., Toth, P., & Baldoquin, M. G. (2014a). A hybrid granular tabu search algorithm for the multi-depot vehicle routing problem. Journal of Heuristics, 20(5), 483-509.
Escobar, J. W., Linfati, R., Baldoquin, M. G., & Toth, P. (2014b). A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem. Transportation Research Part B: Methodological, 67, 344-356.
Escobar, J. W., Linfati, R., & Adarme-Jaimes, W. (2015). A hybrid metaheuristic algorithm for the capacitated location routing problem. Dyna, 82(189), 243-251.
Garc?a-N?jera, A., Bullinaria, J. A., & Gutiérrez-Andrade, M. A. (2015). An evolutionary approach for multi-objective vehicle routing problems with backhauls. Computers & Industrial Engineering, 81, 90-108.
Gutjahr, W. J. (2002). ACO algorithms with guaranteed convergence to the optimal solution. Information Processing Letters, 82(3), 145-153.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2008). Multi-objective vehicle routing problems. European Journal of Operational Research, 189(2), 293-309.
Lau, H. C., Chan, T. M., Tsui, W. T., Chan, F. T., Ho, G. T., & Choy, K. L. (2009). A fuzzy guided multi-objective evolutionary algorithm model for solving transportation problem. Expert Systems with Applications, 36(4), 8255-8268.
Liu, C. M., Chang, T. C., & Huang, L. F. (2006). Multi-objective heuristics for the vehicle routing problem. International Journal of Operations Research, 3(3), 173-181.
Min, H., Current, J., & Schilling, D. (1992). The multiple depot vehicle routing problem with backhauling. Journal of Business Logistics, 13(1), 259.
Mohammadi, M., Tavakkoli-Moghaddam, R., & Rostami, R. (2011). A multi-objective imperialist competitive algorithm for a capacitated hub covering location problem. International Journal of Industrial Engineering Computations, 2(3), 671-688.
Mortezaei, M., & JabalAmeli, M. (2011). A hybrid model for multi-objective capacitated facility location network design problem. International Journal of Industrial Engineering Computations, 2(3), 509-524.
Nezhad, A., Roghanian, E., & Azadi, Z. (2013). A fuzzy goal programming approach to solve multi-objective supply chain network design problems. International Journal of Industrial Engineering Computations, 4(3), 315-324.
Rao, R., & Patel, V. (2014). A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems. International Journal of Industrial Engineering Computations, 5(1), 1-22.
Ropke, S., & Pisinger, D. (2006). A unified heuristic for a large class of vehicle routing problems with backhauls. European Journal of Operational Research, 171(3), 750-775.
Salhi, S., & Nagy, G. (1999). A cluster insertion heuristic for single and multiple depot vehicle routing problems with backhauling. Journal of the Operational Research Society, 50(10), 1034-1042.
Wade, A., & Salhi, S. (2001, July). An ant system algorithm for the vehicle routing problem with backhauls. In MIC?2001––4th Metaheuristic International Conference.
Wade, A., & Salhi, S. (2004). An ant system algorithm for the mixed vehicle routing problem with backhauls. In Metaheuristics: computer decision-making (pp. 699-719). Springer US.
Yalc?n, G. D., & Erginel, N. (2015). Fuzzy multi-objective programming algorithm for vehicle routing problems with backhauls. Expert Systems with Applications, 42(13), 5632-5644.
Yazdian, S., & Shahanaghi, K. (2011). A multi-objective possibilistic programming approach for locating distribution centers and allocating customers demands in supply chains. International Journal of Industrial Engineering Computations, 2(1), 193-202.
Zhou, A., Qu, B. Y., Li, H., Zhao, S. Z., Suganthan, P. N., & Zhang, Q. (2011). Multiobjective evolutionary algorithms: A survey of the state of the art. Swarm and Evolutionary Computation, 1(1), 32-49.