A Hybrid Monte Carlo Local Branching Algorithm for the Single Vehicle Routing Problem with Stochastic Demands

References

• Bertsimas D. A vehicle routing problem with stochastic demand. Oper. Res. (1992) 40(3):574–585Link, Google Scholar
• Bertsimas D., Simchi-Levi D. A new generation of vehicle routing research: Robust algorithms, addressing uncertainty. Oper. Res. (1996) 44(2):286–304Link, Google Scholar
• Bertsimas D., Chervi P., Peterson M. Computational approaches to stochastic vehicle routing problems. Transportation Sci. (1995) 29(4):342–352Link, Google Scholar
• Bianchi L., Birattari M., Chiarandini M., Manfrin M., Mastrolilli M., Paquete L., Rossi-Doria O., Schiavinotto T. Hybrid metaheuristics for the vehicle routing problem with stochastic demands. (2005) . Technical report, IDSIA-06-05, Dalle Molle Institute for Artificial Intelligence, Manno, SwitzerlandGoogle Scholar
• Chepuri K., Hommem-De-Mello T. Solving the vehicle routing problem with stochastic demands using the cross-entropy method. Ann. Oper. Res. (2005) 134:153–181Crossref, Google Scholar
• Dantzig G. B., Ramser J. H. The truck dispatching problem. Management Sci. (1959) 6(1):80–91Link, Google Scholar
• Dror M., Laporte G., Trudeau P. Vehicle routing with stochastic demands: Properties and solution frameworks. Transportation Sci. (1989) 23(3):166–176Link, Google Scholar
• Fischetti M., Lodi A. Local branching. Math. Programming (2003) 98:23–47Crossref, Google Scholar
• Gendreau M., Laporte G., Séguin R. An exact algorithm for the vehicle routing problem with stochastic demands and customers. Transportation Sci. (1995) 29(2):143–155Link, Google Scholar
• Gendreau M., Laporte G., Séguin R. A tabu search heuristic for the vehicle routing problem with stochastic demands and customers. Oper. Res. (1996) 44(3):469–477Link, Google Scholar
• Gutin G., Punnen A. P.The Traveling Salesman Problem and Its Variations (2002) (Kluwer Academic Publishers, Dordrecht, The Netherlands) Google Scholar
• Hjorring C., Holt J. New optimality cuts for a single-vehicle stochastic routing problem. Ann. Oper. Res. (1999) 86:569–584Crossref, Google Scholar
• Kleywegt A. J., Shapiro A., Hommem-De-Mello T. The sample average approximation method for stochastic discrete optimization. SIAM J. Optim. (2001) 12(2):479–502Crossref, Google Scholar
• Laporte G., Louveaux F. The integer L-shaped method for stochastic integer programs with complete recourse. Oper. Res. Lett. (1993) 13:133–142Crossref, Google Scholar
• Laporte G., Louveaux F. V., Van Hamme L. An integer L-shape algorithm for the capacitated vehicle routing problem with stochastic demands. Oper. Res. (2002) 50(3):415–423Link, Google Scholar
• Linderoth J., Shapiro A., Wright S. The empirical behavior of sampling methods for stochastic programming. Ann. Oper. Res. (2006) 142:215–241Crossref, Google Scholar
• Louveaux F., Labbe M., Laporte G., Tanczos K., Toint P. An introduction to stochastic transportation models. Operations Research and Decision Aid Methodologies in Traffic and Transportation Management, Vol. 166, Computer and Systems Sciences (1998) (Springer-Verlag, Heidelberg, Germany) 244–263Crossref, Google Scholar
• Lysgaard J., Letchford A. N., Eglese R. W. A new branch-and-cut algorithm for the capacitated vehicle routing problem. Math. Programming (2004) 100:423–445Crossref, Google Scholar
• Rei W. Accélération de méthodes classiques par l'utilisation de stratégies de séparation locale comme outil d'hybridation. (2007) . Unpublished doctoral dissertation, Département d'Informatique et de Recherche Opérationelle, Université de Montréal, Montréal, QuébecGoogle Scholar
• Rei W., Gendreau M., Soriano P. Local branching cuts for the 0–1 integer L-shaped algorithm. (2007) . Techical report, CIRRELT-2007-23, Centre Interuniversitaire de Recherche sur les Réseaux d'Entreprise, la Logistique et le Transport (CIRRELT), Montréal, QuébecGoogle Scholar
• Santoso T., Ahmed S., Goetschalckx M., Shapiro A. A stochastic programming approach for supply chain network design under uncertainty. Eur. J. Oper. Res. (2005) 167:96–115Crossref, Google Scholar
• Secomandi N. Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands. Comput. Oper. Res. (2000) 27:1201–1225Crossref, Google Scholar
• Secomandi N. A rollout policy for the vehicle routing problem with stochastic demands. Oper. Res. (2001) 49(5):796–802Link, Google Scholar
• Secomandi N., Margot F. Reoptimization approaches for the vehicle-routing problem with stochastic demands. Oper. Res. (2008) 57(1):214–230Link, Google Scholar
• Toth P., Vigo D.The Vehicle Routing Problem, SIAM, Monographs on Discrete Mathematics and Applications (2001) (Society for Industrial and Applied Mathematics, Philadelphia) Google Scholar
• Verweij B., Ahmed S., Kleywegt A. J., Nemhauser G., Shapiro A. The sample average approximation method applied to stochastic routing problems: A computational study. Computational Optim. Appl. (2003) 24:289–333Crossref, Google Scholar
• Yang W., Mathur K., Ballou R. H. Stochastic vehicle routing problem with restocking. Transportation Sci. (2000) 34(1):99–112Link, Google Scholar