How to cite this paper
APA: Londoño, A., González, W., Giraldo, O & Escobar, J. (2024). A hybrid heuristic approach for the multi-objective multi depot vehicle routing problem. International Journal of Industrial Engineering Computations, 15(1), 337-354.
Chicago/Turabian: Londoño, A., González, W., Giraldo, O & Escobar, J. 2024. "A hybrid heuristic approach for the multi-objective multi depot vehicle routing problem." International Journal of Industrial Engineering Computations 15, no. 1 (2024): 337-354.
AMA: Londoño, A., González, W., Giraldo, O & Escobar, J. A hybrid heuristic approach for the multi-objective multi depot vehicle routing problem. International Journal of Industrial Engineering Computations. 2024;15(1):337-354.
References
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Chao, I. M., Golden, B. L., & Wasil, E. (1993). A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions. American Journal of Mathematical and Management Sciences, 13(3-4), 371-406.
Chu, P. C., & Beasley, J. E. (1997). A genetic algorithm for the generalised assignment problem. Computers & Operations Research, 24(1), 17-23.
de Oliveira, F. B., Enayatifar, R., Sadaei, H. J., Guimarães, F. G., & Potvin, J. Y. (2016). A cooperative coevolutionary algorithm for the multi-depot vehicle routing problem. Expert Systems with Applications, 43, 117-130.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Escobar, J. W., Linfati, R., Toth, P., & Baldoquin, M. G. (2014). A hybrid granular tabu search algorithm for the multi-depot vehicle routing problem. Journal of heuristics, 20, 483-509.
Filipec, M., Škrlec, D., & Krajcar, S. (2000). Genetic algorithm approach for multiple depot capacitated vehicle routing problem solving with heuristic improvements. International Journal of Modelling and Simulation, 20(4), 320-328.
Galindres-Guancha, L., Toro-Ocampo, E., & Rendón, R. (2018). Multi-objective MDVRP solution considering route balance and cost using the ILS metaheuristic. International Journal of Industrial Engineering Computations, 9(1), 33-46.
Garcia-Najera, A., & Bullinaria, J. A. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287-300.
Geetha, S., Vanathi, P. T., & Poonthalir, G. (2012). Metaheuristic approach for the multi-depot vehicle routing problem. Applied Artificial Intelligence, 26(9), 878-901.
Ho, W., Ho, G. T., Ji, P., & Lau, H. C. (2008). A hybrid genetic algorithm for the multi-depot vehicle routing problem. Engineering applications of artificial intelligence, 21(4), 548-557.
Hou, D., Fan, H., & Ren, X. (2021). Multi-Depot Joint Distribution Vehicle Routing Problem Considering Energy Consumption with Time-Dependent Networks. Symmetry, 13(11), 2082.
Hou, D., Fan, H., Ren, X., Tian, P., & Lv, Y. (2021). Time-dependent multi-depot heterogeneous vehicle routing problem considering temporal–spatial distance. Sustainability, 13(9), 4674.
Jayarathna, D. G. N. D., Lanel, G. H. J., & Juman, Z. A. M. S. (2021). Survey on ten years of multi-depot vehicle routing problems: mathematical models, solution methods and real-life applications. Sustainable Development Research, 3(1), p36-p36.
Jayarathna, N., Lanel, J., & Juman, Z. (2020). View of Five years of multi-depot vehicle routing problems. Journal of Sustainable Development Transport and Logistics, 109-123.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2007). Target aiming Pareto search and its application to the vehicle routing problem with route balancing. Journal of Heuristics, 13, 455-469.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.
Karakatič, S., & Podgorelec, V. (2015). A survey of genetic algorithms for solving multi depot vehicle routing problem. Applied Soft Computing, 27, 519-532.
Li, Y., Qian, B., Hu, R., Wu, L. P., & Liu, B. (2019). Two-stage algorithm for solving multi-depot green vehicle routing problem with time window. In Intelligent Computing Theories and Application: 15th International Conference, ICIC 2019, Nanchang, China, August 3–6, 2019, Proceedings, Part I 15 (pp. 665-675). Springer International Publishing.
Li, Y., Soleimani, H., & Zohal, M. (2019b). An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives. Journal of cleaner production, 227, 1161-1172.
Liu, R., Jiang, Z., & Geng, N. (2014). A hybrid genetic algorithm for the multi-depot open vehicle routing problem. OR spectrum, 36, 401-421.
Luo, J., & Chen, M. R. (2014). Improved shuffled frog leaping algorithm and its multi-phase model for multi-depot vehicle routing problem. Expert Systems with Applications, 41(5), 2535-2545.
Luo, J., Li, X., & Chen, M. R. (2012). A Novel Meta-heuristic for the Multi-depot Vehicle Routing Problem. In Information Computing and Applications: Third International Conference, ICICA 2012, Chengde, China, September 14-16, 2012. Proceedings, Part I 3 (pp. 216-224). Springer Berlin Heidelberg.
Mancini, S., Gansterer, M., & Hartl, R. F. (2021). The collaborative consistent vehicle routing problem with workload balance. European journal of operational research, 293(3), 955-965.
Matl, P., Hartl, R. F., & Vidal, T. (2018). Workload equity in vehicle routing problems: A survey and analysis. Transportation Science, 52(2), 239-260.
Mirabi, M. (2014). A hybrid electromagnetism algorithm for multi-depot periodic vehicle routing problem. The International Journal of Advanced Manufacturing Technology, 71(1-4), 509-518.
Montoya, O. D., Gil-González, W., & Orozco-Henao, C. (2020). Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach. Engineering Science and Technology, an International Journal, 23(6), 1351-1363.
Moonsri, K., Sethanan, K., Worasan, K., & Nitisiri, K. (2021). A hybrid and self-adaptive differential evolution algorithm for the multi-depot vehicle routing problem in egg distribution. Applied Sciences, 12(1), 35.
Networking and Emerging Optimization. (2006). The VRP web. Retrieved from https://www.bernabe.dorronsoro.es/vrp/index.html?/Problem_Instances/CVRPTWInstances.html
Ombuki-Berman, B., & Hanshar, F. T. (2009). Using genetic algorithms for multi-depot vehicle routing. In Bio-inspired algorithms for the vehicle routing problem (pp. 77-99). Berlin, Heidelberg: Springer Berlin Heidelberg.
Peng, B., Wu, L., Yi, Y., & Chen, X. (2020). Solving the multi-depot green vehicle routing problem by a hybrid evolutionary algorithm. Sustainability, 12(5), 2127.
Prabu, U., Ravisasthiri, P., Sriram, R., Malarvizhi, N., & Amudhavel, J. (2019). EODVGA: an enhanced ODV based genetic algorithm for multi-depot vehicle routing problem. EAI Endorsed Transactions on Scalable Information Systems, 6(21), e8-e8.
Renaud, J., Laporte, G., & Boctor, F. F. (1996). A tabu search heuristic for the multi-depot vehicle routing problem. Computers & Operations Research, 23(3), 229-235.
Shen, L., Tao, F., & Wang, S. (2018). Multi-depot open vehicle routing problem with time windows based on carbon trading. International journal of environmental research and public health, 15(9), 2025.
Singh, V., Ganapathy, L., & Pundir, A. K. (2021). An improved genetic algorithm for solving multi depot Vehicle Routing Problems. In Research anthology on multi-industry uses of genetic programming and algorithms (pp. 375-402). IGI Global.
Skok, M., Skrlec, D., & Krajcar, S. (2000, August). The genetic algorithm method for multiple depot capacitated vehicle routing problem solving. In KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No. 00TH8516) (Vol. 2, pp. 520-526). IEEE.
Subramanian, A., Uchoa, E., & Ochi, L. S. (2013). A hybrid algorithm for a class of vehicle routing problems. Computers & Operations Research, 40(10), 2519-2531.
Surekha, P., & Sumathi, S. (2011). Solution to multi-depot vehicle routing problem using genetic algorithms. World Applied Programming, 1(3), 118-131.
Tang, Y. L., Cai, Y. G., & Yang, Q. J. (2015). Optimization of Multi-Depot Heterogeneous Incident Vehicle Routing Problem with Soft Time Windows based on an Improved Ant Colony Optimization. Advanced Materials Research, 1061, 1108-1117.
Wink, S., Bäck, T., & Emmerich, M. (2012, June). A meta-genetic algorithm for solving the capacitated vehicle routing problem. In 2012 IEEE congress on evolutionary computation (pp. 1-8). IEEE.
Yu, V. F., Aloina, G., Susanto, H., Effendi, M. K., & Lin, S. W. (2022). Regional Location Routing Problem for Waste Collection Using Hybrid Genetic Algorithm-Simulated Annealing. Mathematics, 10(12), 2131.
Yücenur, G. N., & Demirel, N. Ç. (2011). A new geometric shape-based genetic clustering algorithm for the multi-depot vehicle routing problem. Expert Systems with Applications, 38(9), 11859-11865.
Zacharia, P., Drosos, C., Piromalis, D., & Papoutsidakis, M. (2021). The vehicle routing problem with fuzzy payloads considering fuel consumption. Applied Artificial Intelligence, 35(15), 1755-1776.
Zhang, W., Gajpal, Y., Appadoo, S. S., & Wei, Q. (2020). Multi-depot green vehicle routing problem to minimize carbon emissions. Sustainability, 12(8), 3500.
Zhou, W., Song, T., He, F., & Liu, X. (2013). Multiobjective vehicle routing problem with route balance based on genetic algorithm. discrete Dynamics in Nature and Society, 2013.
Zhou, Z., Ha, M., Hu, H., & Ma, H. (2021). Half open multi-depot heterogeneous vehicle routing problem for hazardous materials transportation. Sustainability, 13(3), 1262.
Chao, I. M., Golden, B. L., & Wasil, E. (1993). A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions. American Journal of Mathematical and Management Sciences, 13(3-4), 371-406.
Chu, P. C., & Beasley, J. E. (1997). A genetic algorithm for the generalised assignment problem. Computers & Operations Research, 24(1), 17-23.
de Oliveira, F. B., Enayatifar, R., Sadaei, H. J., Guimarães, F. G., & Potvin, J. Y. (2016). A cooperative coevolutionary algorithm for the multi-depot vehicle routing problem. Expert Systems with Applications, 43, 117-130.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Escobar, J. W., Linfati, R., Toth, P., & Baldoquin, M. G. (2014). A hybrid granular tabu search algorithm for the multi-depot vehicle routing problem. Journal of heuristics, 20, 483-509.
Filipec, M., Škrlec, D., & Krajcar, S. (2000). Genetic algorithm approach for multiple depot capacitated vehicle routing problem solving with heuristic improvements. International Journal of Modelling and Simulation, 20(4), 320-328.
Galindres-Guancha, L., Toro-Ocampo, E., & Rendón, R. (2018). Multi-objective MDVRP solution considering route balance and cost using the ILS metaheuristic. International Journal of Industrial Engineering Computations, 9(1), 33-46.
Garcia-Najera, A., & Bullinaria, J. A. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287-300.
Geetha, S., Vanathi, P. T., & Poonthalir, G. (2012). Metaheuristic approach for the multi-depot vehicle routing problem. Applied Artificial Intelligence, 26(9), 878-901.
Ho, W., Ho, G. T., Ji, P., & Lau, H. C. (2008). A hybrid genetic algorithm for the multi-depot vehicle routing problem. Engineering applications of artificial intelligence, 21(4), 548-557.
Hou, D., Fan, H., & Ren, X. (2021). Multi-Depot Joint Distribution Vehicle Routing Problem Considering Energy Consumption with Time-Dependent Networks. Symmetry, 13(11), 2082.
Hou, D., Fan, H., Ren, X., Tian, P., & Lv, Y. (2021). Time-dependent multi-depot heterogeneous vehicle routing problem considering temporal–spatial distance. Sustainability, 13(9), 4674.
Jayarathna, D. G. N. D., Lanel, G. H. J., & Juman, Z. A. M. S. (2021). Survey on ten years of multi-depot vehicle routing problems: mathematical models, solution methods and real-life applications. Sustainable Development Research, 3(1), p36-p36.
Jayarathna, N., Lanel, J., & Juman, Z. (2020). View of Five years of multi-depot vehicle routing problems. Journal of Sustainable Development Transport and Logistics, 109-123.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2007). Target aiming Pareto search and its application to the vehicle routing problem with route balancing. Journal of Heuristics, 13, 455-469.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.
Karakatič, S., & Podgorelec, V. (2015). A survey of genetic algorithms for solving multi depot vehicle routing problem. Applied Soft Computing, 27, 519-532.
Li, Y., Qian, B., Hu, R., Wu, L. P., & Liu, B. (2019). Two-stage algorithm for solving multi-depot green vehicle routing problem with time window. In Intelligent Computing Theories and Application: 15th International Conference, ICIC 2019, Nanchang, China, August 3–6, 2019, Proceedings, Part I 15 (pp. 665-675). Springer International Publishing.
Li, Y., Soleimani, H., & Zohal, M. (2019b). An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives. Journal of cleaner production, 227, 1161-1172.
Liu, R., Jiang, Z., & Geng, N. (2014). A hybrid genetic algorithm for the multi-depot open vehicle routing problem. OR spectrum, 36, 401-421.
Luo, J., & Chen, M. R. (2014). Improved shuffled frog leaping algorithm and its multi-phase model for multi-depot vehicle routing problem. Expert Systems with Applications, 41(5), 2535-2545.
Luo, J., Li, X., & Chen, M. R. (2012). A Novel Meta-heuristic for the Multi-depot Vehicle Routing Problem. In Information Computing and Applications: Third International Conference, ICICA 2012, Chengde, China, September 14-16, 2012. Proceedings, Part I 3 (pp. 216-224). Springer Berlin Heidelberg.
Mancini, S., Gansterer, M., & Hartl, R. F. (2021). The collaborative consistent vehicle routing problem with workload balance. European journal of operational research, 293(3), 955-965.
Matl, P., Hartl, R. F., & Vidal, T. (2018). Workload equity in vehicle routing problems: A survey and analysis. Transportation Science, 52(2), 239-260.
Mirabi, M. (2014). A hybrid electromagnetism algorithm for multi-depot periodic vehicle routing problem. The International Journal of Advanced Manufacturing Technology, 71(1-4), 509-518.
Montoya, O. D., Gil-González, W., & Orozco-Henao, C. (2020). Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach. Engineering Science and Technology, an International Journal, 23(6), 1351-1363.
Moonsri, K., Sethanan, K., Worasan, K., & Nitisiri, K. (2021). A hybrid and self-adaptive differential evolution algorithm for the multi-depot vehicle routing problem in egg distribution. Applied Sciences, 12(1), 35.
Networking and Emerging Optimization. (2006). The VRP web. Retrieved from https://www.bernabe.dorronsoro.es/vrp/index.html?/Problem_Instances/CVRPTWInstances.html
Ombuki-Berman, B., & Hanshar, F. T. (2009). Using genetic algorithms for multi-depot vehicle routing. In Bio-inspired algorithms for the vehicle routing problem (pp. 77-99). Berlin, Heidelberg: Springer Berlin Heidelberg.
Peng, B., Wu, L., Yi, Y., & Chen, X. (2020). Solving the multi-depot green vehicle routing problem by a hybrid evolutionary algorithm. Sustainability, 12(5), 2127.
Prabu, U., Ravisasthiri, P., Sriram, R., Malarvizhi, N., & Amudhavel, J. (2019). EODVGA: an enhanced ODV based genetic algorithm for multi-depot vehicle routing problem. EAI Endorsed Transactions on Scalable Information Systems, 6(21), e8-e8.
Renaud, J., Laporte, G., & Boctor, F. F. (1996). A tabu search heuristic for the multi-depot vehicle routing problem. Computers & Operations Research, 23(3), 229-235.
Shen, L., Tao, F., & Wang, S. (2018). Multi-depot open vehicle routing problem with time windows based on carbon trading. International journal of environmental research and public health, 15(9), 2025.
Singh, V., Ganapathy, L., & Pundir, A. K. (2021). An improved genetic algorithm for solving multi depot Vehicle Routing Problems. In Research anthology on multi-industry uses of genetic programming and algorithms (pp. 375-402). IGI Global.
Skok, M., Skrlec, D., & Krajcar, S. (2000, August). The genetic algorithm method for multiple depot capacitated vehicle routing problem solving. In KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No. 00TH8516) (Vol. 2, pp. 520-526). IEEE.
Subramanian, A., Uchoa, E., & Ochi, L. S. (2013). A hybrid algorithm for a class of vehicle routing problems. Computers & Operations Research, 40(10), 2519-2531.
Surekha, P., & Sumathi, S. (2011). Solution to multi-depot vehicle routing problem using genetic algorithms. World Applied Programming, 1(3), 118-131.
Tang, Y. L., Cai, Y. G., & Yang, Q. J. (2015). Optimization of Multi-Depot Heterogeneous Incident Vehicle Routing Problem with Soft Time Windows based on an Improved Ant Colony Optimization. Advanced Materials Research, 1061, 1108-1117.
Wink, S., Bäck, T., & Emmerich, M. (2012, June). A meta-genetic algorithm for solving the capacitated vehicle routing problem. In 2012 IEEE congress on evolutionary computation (pp. 1-8). IEEE.
Yu, V. F., Aloina, G., Susanto, H., Effendi, M. K., & Lin, S. W. (2022). Regional Location Routing Problem for Waste Collection Using Hybrid Genetic Algorithm-Simulated Annealing. Mathematics, 10(12), 2131.
Yücenur, G. N., & Demirel, N. Ç. (2011). A new geometric shape-based genetic clustering algorithm for the multi-depot vehicle routing problem. Expert Systems with Applications, 38(9), 11859-11865.
Zacharia, P., Drosos, C., Piromalis, D., & Papoutsidakis, M. (2021). The vehicle routing problem with fuzzy payloads considering fuel consumption. Applied Artificial Intelligence, 35(15), 1755-1776.
Zhang, W., Gajpal, Y., Appadoo, S. S., & Wei, Q. (2020). Multi-depot green vehicle routing problem to minimize carbon emissions. Sustainability, 12(8), 3500.
Zhou, W., Song, T., He, F., & Liu, X. (2013). Multiobjective vehicle routing problem with route balance based on genetic algorithm. discrete Dynamics in Nature and Society, 2013.
Zhou, Z., Ha, M., Hu, H., & Ma, H. (2021). Half open multi-depot heterogeneous vehicle routing problem for hazardous materials transportation. Sustainability, 13(3), 1262.