References
- Altabeeb, A. M., A. M. Mohsen, and A. Ghallab. 2019. An improved hybrid firefly algorithm for capacitated vehicle routing problem. Applied Soft Computing 84:1–9. doi:https://doi.org/10.1016/j.asoc.2019.105728.
- Asgharia, M., and S. M. J. Mirzapour Al-e-hashem. 2021. Green vehicle routing problem: A state-of-the-art review. International Journal of Production Economics 231: 107899.
- Barma, P. S., J. Dutta, and A. Mukherjee. 2019. A 2-opt guided discrete antlion optimization algorithm for multi-depot vehicle routing problem, Decision Making. Applications in Management and Engineering 2 (2):112–25.
- Basso, R., B. Kulcsár, B. Egardt, P. Lindroth, and I. Sanchez-Diaz. 2019. Energy consumption estimation integrated into the Electric Vehicle Routing Problem. Transportation Research Part D: Transport and Environment 69:141–67. doi:https://doi.org/10.1016/j.trd.2019.01.006.
- Bruglieri, M., S. Mancini, F. Pezzella, and O. Pisacane. 2019. A path-based solution approach for the Green Vehicle Routing Problem. Computers & Operations Research 103:109–22. doi:https://doi.org/10.1016/j.cor.2018.10.019.
- Christofides, N., and S. Eilon. 1969. An algorithm for the vehicle dispatching problem. Journal of the Operational Research Society 20 (3):309–18. doi:https://doi.org/10.1057/jors.1969.75.
- Dantzig, G. B., and J. H. Ramser. 1959. The truck dispatching problem. Manage. Sci 6 (1):80–91. doi:https://doi.org/10.1287/mnsc.6.1.80.
- Elshaer, R., and H. Awad. 2020. A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants. Computers & Industrial Engineering 140: 106242.
- Erbao, C., and L. Mingyong. 2009. A hybrid differential evolution algorithm to vehicle routing problem with fuzzy demands. Journal of Computational and Applied Mathematics 231 (1):302–10. doi:https://doi.org/10.1016/j.cam.2009.02.015.
- Fukasawa, R., Q. He, and Y. Song. 2016. A Branch-Cut-and-Price Algorithm for the Energy Minimization Vehicle Routing Problem. Transportation Science 50 (1):23–34. doi:https://doi.org/10.1287/trsc.2015.0593.
- Gaur, D. R., A. Mudgal, and R. R. Singh. 2013. Routing vehicles to minimize fuel consumption. Operations Research Letters 41 (6):576–80. doi:https://doi.org/10.1016/j.orl.2013.07.007.
- Ghaffari-Nasab, N., S. G. Ahari, and M. Ghazanfari. 2013. A hybrid simulated annealing based heuristic for solving the location-routing problem with fuzzy demands. Scientia Iranica 20 (3):919–30.
- Ghannadpour, S. F., S. Noori, R. Tavakkoli-Moghaddam, and K. Ghoseiri. 2014. A multi-objective dynamic vehicle routing problem with fuzzy time windows: Model, solution and application. Applied Soft Computing 14:504–27. doi:https://doi.org/10.1016/j.asoc.2013.08.015.
- Goldberg, D. 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison-Wesley.
- Huang, Y.-H., C. A. Blazquez, S.-H. Huang, and G. Paredes-Belmar. 2019. Latorre-Nuñez G. 2019. Solving the Feeder Vehicle Routing Problem using ant colony optimization. Computers & Industrial Engineering 127:520–35. doi:https://doi.org/10.1016/j.cie.2018.10.037.
- Jianyu, L., S. Zhenzhong, P. M. Pardalos, H. Ying, Z. Shaohui, and L. Chuan. 2019. A hybrid multi-objective genetic local search algorithm for the prize-collecting vehicle routing problem. Information Sciences 478:40–61. doi:https://doi.org/10.1016/j.ins.2018.11.006.
- Kara, I., B. Y. Kara, and M. K. Yetis. 2007. Energy minimizing vehicle routing problem. International Conference on Combinatorial Optimization, COCOCA 2007, Xian, China. A.Press,Y. Xu and B. Zhu (Eds.), COCOA 2007, LNCS, 4616: 62–67.
- Kara, I., B. Y. Kara, and M. K. Yetis. 2008. Cumulative vehicle routing problems. C. Tonic and G. Hrvoje, Eds. 85–98. Vienna, Austria: InTech
- Keskin, M., G. Laporte, and B. Çatay. 2019. Electric Vehicle Routing Problem with Time-Dependent Waiting Times at Recharging Stations. Computers & Operations Research 107:77–94. doi:https://doi.org/10.1016/j.cor.2019.02.014.
- Kuo, R. J., and F. E. Zulvia. 2017. Hybrid genetic ant colony optimization algorithm for capacitated vehicle routing problem with fuzzy demand – A case study on garbage collection system. 4th International Conference on Industrial Engineering and Applications,Nagoya, Japan.
- Li, Y., H. Soleimani, and M. Zohal. 2019. An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives. Journal of Cleaner Production 227:1161–72. doi:https://doi.org/10.1016/j.jclepro.2019.03.185.
- Liou, T., and M. J. Wang. 1992. Ranking fuzzy numbers with integral value. Fuzzy Sets and Systems 50 (3):247–55. doi:https://doi.org/10.1016/0165-0114(92)90223-Q.
- Liu, B. 2004. Uncertain theory: An introduction to its axiomatic foundations. Berlin: Springer.
- López-Castro, L. F., and J. R. Montoya-Torres, Vehicle routing with fuzzy time windows using a genetic algorithm, 2011 IEEE Workshop On Computational Intelligence In Production And Logistics Systems (CIPLS), Paris, France.
- Majumdar, J., and A. K. Bhunia. 2011. Genetic algorithm for asymmetric traveling salesman problem with imprecise travel times. Journal of Computational and Applied Mathematics 235 (9):3063–78. doi:https://doi.org/10.1016/j.cam.2010.12.027.
- Marković, D., G. Petrović, Z. Ćojbašić, and A. Stanković. 2020. The vehicle routing problem with stochastic denands in an urban area – A case study. FACTA UNIVERSITATIS Series: Mechanical Engineering 18 (1):107–20. doi:https://doi.org/10.22190/FUME190318021M.
- Michalewitz Z. 1996. Genetic Algorithms + Data Structures = Evolution Programs. 3rd edition, Springer-Verlag. Berlin, Heidelberg.
- Moghdani, R., K. Salimifard, E. Demir, and A. Benyettou. 2021. The green vehicle routing problem: A systematic literature review. Journal of Cleaner Production 279:1–19. doi:https://doi.org/10.1016/j.jclepro.2020.123691.
- Oyola, J., H. Arntzen, and D. Woodruff. 2017. The stochastic vehicle routing problem, a literature review, Part II: Solution methods. EURO Journal on Transportation and Logistics 6 (4):349–88. doi:https://doi.org/10.1007/s13676-016-0099-7.
- Pamucar, D. 2020. Normalized weighted geometric Dombi Bonferroni mean operator with interval grey numbers: Application in multicriteria decision making. Reports in Mechanical Engineering 1 (1):1. doi:https://doi.org/10.31181/rme200101044p.
- Pamucar, D., and A. Janković. 2020. The application of the hybrid interval rough weighted Power-Heronian operator in multi-criteria decision making. Operational Research in Engineering Sciences: Theory and Applications 3:2.
- Pelletier, S., O. Jabali, and G. Laporte. 2019. The electric vehicle routing problem with energy consumption uncertainty. Transportation Research Part B: Methodological 126:225–55. doi:https://doi.org/10.1016/j.trb.2019.06.006.
- Queiroga, E., R. Sadykov, and E. Uchoa. 2021. A POPMUSIC matheuristic for the capacitated vehicle routing problem. Computers & Operations Research 136:1–14. doi:https://doi.org/10.1016/j.cor.2021.105475.
- Wang, R., J. Zhou, X. Li, and A. A. Pantelous. 2019. Solving the green fuzzy vehicle routing problem using a revised hybrid intelligent algorithm. Journal of Ambient Intelligence and Humanized Computing 10 (1):321–32. doi:https://doi.org/10.1007/s12652-018-0703-9.
- Wang, S., M. Liu, and F. Chu. 2020. Approximate and exact algorithms for an energy minimization traveling salesman problem. Journal of Cleaner Production 249:1–17. doi:https://doi.org/10.1016/j.jclepro.2019.119433.
- Wang, Y., L. Wang, G. Chen, Z. Cai, Y. Zhou, and L. Xing. 2020. An Improved Ant Colony Optimization algorithm to the Periodic Vehicle Routing Problem with Time Window and Service Choice. Swarm and Evolutionary Computation 55:1–15. doi:https://doi.org/10.1016/j.swevo.2020.100675.
- Xiao, Y., O. Zhao, I. Kaku, and Y. Xu. 2012. Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Computers & Operations Research 39 (7):1419–31. doi:https://doi.org/10.1016/j.cor.2011.08.013.
- Xidias, E., and P. Azariadis 2019. Energy Efficient Motion Design and Task Scheduling for an Autonomous Vehicle. Proceedings of the Design Society: International Conference on Engineering 1( 1): 2853–62, Chania Crete, Greece: Cambridge University Press.
- Zacharia, P. T., and E. K. Xidias. 2020. AGV Routing and Motion Planning in a Flexible Manufacturing System using a Fuzzy-based Genetic Algorithm. The International Journal of Advanced Manufacturing Technology 109 (7–8):1801–13. doi:https://doi.org/10.1007/s00170-020-05755-3.
- Zadeh, L. A. 1965. Fuzzy sets. Information and Control 8 (3):338–53. doi:https://doi.org/10.1016/S0019-9958(65)90241-X.
- Zarandi, M. H. F., A. Hemmati, and S. Davari. 2011. The multi-depot capacitated location-routing problem with fuzzy travel times. Expert Systems with Applications 38 (8):10075–84. doi:https://doi.org/10.1016/j.eswa.2011.02.006.
- Zheng, Y., and B. Liu. 2006. Fuzzy vehicle routing model with credibility measure and its hybrid intelligent algorithm. Applied Mathematics and Computation 176 (2):673–83. doi:https://doi.org/10.1016/j.amc.2005.10.013.