[1] Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management Science, 6(1), 80–91. https://doi.org/10.1287/mnsc.6.1.80
[2] Laporte, G. (2009). Fifty years of vehicle routing. Transportation Science, 43(4), 408–416. https://doi.org/10.1287/trsc.1090.0301
[3] Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: Problems, methods, and applications (2nd ed.). SIAM. https://doi.org/10.1137/1.9781611973594
[4] Dantzig, G. B. (1963). Linear programming and extensions. Princeton University Press. https://doi.org/10.1515/9781400884179
[5] Ahuja, R. K., Magnanti, T. L., & Orlin, J. B. (1993). Network flows: Theory, algorithms, and applications. Prentice Hall.
[6] Lenstra, J. K., & Rinnooy Kan, A. H. G. (1981). Complexity of vehicle routing and scheduling problems. Networks, 11(2), 221–227. https://doi.org/10.1002/net.3230110211
[7] Cordeau, J.-F., Gendreau, M., Laporte, G., Potvin, J.-Y., & Semet, F. (2002). A guide to vehicle routing heuristics. Journal of the Operational Research Society, 53(5), 512–522. https://doi.org/10.1057/palgrave.jors.2601319
[8] Vidal, T., Crainic, T. G., Gendreau, M., & Prins, C. (2013). Heuristics for multi-attribute vehicle routing problems: A survey and synthesis. European Journal of Operational Research, 231(1), 1–21. https://doi.org/10.1016/j.ejor.2013.02.053
[9] Braekers, K., Ramaekers, K., & Van Nieuwenhuyse, I. (2016). The vehicle routing problem: State of the art classification and review. Computers & Industrial Engineering, 99, 300–313. https://doi.org/10.1016/j.cie.2015.12.007
[10] Hooker, J. N. (1995). Testing heuristics: We have it all wrong. Journal of Heuristics, 1(1), 33–42. https://doi.org/10.1007/BF02430364
[11] Sörensen, K. (2015). Metaheuristics—the metaphor exposed. International Transactions in Operational Research, 22(1), 3–18. https://doi.org/10.1111/itor.12001
[12] Kantorovich, L. V. (1960). Mathematical methods of organizing and planning production. Management Science, 6(4), 366–422. https://doi.org/10.1287/mnsc.6.4.366
[13] Karmarkar, N. (1984). A new polynomial-time algorithm for linear programming. Combinatorica, 4(4), 373–395. https://doi.org/10.1007/BF02579150
[14] Bixby, R. E. (2012). A brief history of linear and mixed-integer programming computation. Documenta Mathematica, Extra Volume ISMP, 107–121. https://doi.org/10.4171/dms/6/16
[15] Nocedal, J., & Wright, S. J. (2006). Numerical optimization (2nd ed.). Springer. https://doi.org/10.1007/978-0-387-40065-5
[16] Miller, C. E., Tucker, A. W., & Zemlin, R. A. (1960). Integer programming formulation of traveling salesman problems. Journal of the ACM, 7(4), 326–329. https://doi.org/10.1145/321043.321046
[17] Baldacci, R., Mingozzi, A., & Roberti, R. (2012). Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints. European Journal of Operational Research, 218(1), 1–6. https://doi.org/10.1016/j.ejor.2011.07.037
[18] Pecin, D., Pessoa, A., Poggi, M., & Uchoa, E. (2017). Improved branch-cut-and-price for capacitated vehicle routing. Mathematical Programming Computation, 9(1), 61–100. https://doi.org/10.1007/s12532-016-0108-8
[19] Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35(2), 254–265. https://doi.org/10.1287/opre.35.2.254
[20] Gendreau, M., Laporte, G., & Séguin, R. (1996). Stochastic vehicle routing. European Journal of Operational Research, 88(1), 3–12. https://doi.org/10.1016/0377-2217(95)00050-X
[21] Pillac, V., Gendreau, M., Guéret, C., & Medaglia, A. L. (2013). A review of dynamic vehicle routing problems. European Journal of Operational Research, 225(1), 1–11. https://doi.org/10.1016/j.ejor.2012.08.015
[22] Clarke, G., & Wright, J. W. (1964). Scheduling of vehicles from a central depot to a number of delivery points. Operations Research, 12(4), 568–581. https://doi.org/10.1287/opre.12.4.568
[23] Gillett, B. E., & Miller, L. R. (1974). A heuristic algorithm for the vehicle-dispatch problem. Operations Research, 22(2), 340–349. https://doi.org/10.1287/opre.22.2.340
[24] Blum, C., & Roli, A. (2003). Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys, 35(3), 268–308. https://doi.org/10.1145/937503.937505
[25] Gendreau, M., Hertz, A., & Laporte, G. (1994). A tabu search heuristic for the vehicle routing problem. Management Science, 40(10), 1276–1290. https://doi.org/10.1287/mnsc.40.10.1276
[26] Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680. https://doi.org/10.1126/science.220.4598.671
[27] Ropke, S., & Pisinger, D. (2006). An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transportation Science, 40(4), 455–472. https://doi.org/10.1287/trsc.1050.0135
[28] Holland, J. H. (1975). Adaptation in natural and artificial systems. University of Michigan Press.
[29] Prins, C. (2004). A simple and effective evolutionary algorithm for the vehicle routing problem. Computers & Operations Research, 31(12), 1985–2002. https://doi.org/10.1016/S0305-0548(03)00158-8
[30] Vidal, T., Crainic, T. G., Gendreau, M., Lahrichi, N., & Rei, W. (2012). A hybrid genetic algorithm for multidepot and periodic vehicle routing problems. Operations Research, 60(3), 611–624. https://doi.org/10.1287/opre.1120.1048
[31] Vidal, T. (2022). Hybrid genetic search for the CVRP: Open-source implementation and SWAP* neighborhood. Computers & Operations Research, 140, 105643. https://doi.org/10.1016/j.cor.2021.105643
[32] Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, 26(1), 29–41. https://doi.org/10.1109/3477.484436
[33] Bullnheimer, B., Hartl, R. F., & Strauss, C. (1999). An improved ant system algorithm for the vehicle routing problem. Annals of Operations Research, 89, 319–328. https://doi.org/10.1023/A:1018940026670
[34] Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In Proceedings of the IEEE International Conference on Neural Networks (Vol. 4, pp. 1942–1948). IEEE. https://doi.org/10.1109/ICNN.1995.488968
[35] Accorsi, L., & Vigo, D. (2021). A fast and scalable heuristic for the solution of large-scale capacitated vehicle routing problems. Transportation Science, 55(4), 832–856. https://doi.org/10.1287/trsc.2021.1059
[36] Bengio, Y., Lodi, A., & Prouvost, A. (2021). Machine learning for combinatorial optimization: A methodological tour d’horizon. European Journal of Operational Research, 290(2), 405–421. https://doi.org/10.1016/j.ejor.2020.07.063
[37] Nazari, M., Oroojlooy, A., Snyder, L., & Takáč, M. (2018). Reinforcement learning for solving the vehicle routing problem. Advances in Neural Information Processing Systems, 31.
[38] Kool, W., van Hoof, H., & Welling, M. (2019). Attention, learn to solve routing problems! In International Conference on Learning Representations.
[39] Barr, R. S., Golden, B. L., Kelly, J. P., Resende, M. G. C., & Stewart, W. R. (1995). Designing and reporting on computational experiments with heuristic methods. Journal of Heuristics, 1(1), 9–32. https://doi.org/10.1007/BF02430363
[40] Uchoa, E., Pecin, D., Pessoa, A., Poggi, M., Vidal, T., & Subramanian, A. (2017). New benchmark instances for the capacitated vehicle routing problem. European Journal of Operational Research, 257(3), 845–858. https://doi.org/10.1016/j.ejor.2016.08.012
[41] López-Ibáñez, M., Dubois-Lacoste, J., Pérez Cáceres, L., Birattari, M., & Stützle, T. (2016). The irace package: Iterated racing for automatic algorithm configuration. Operations Research Perspectives, 3, 43–58. https://doi.org/10.1016/j.orp.2016.09.002