Consistent Time Window Assignments for Stochastic Multi-Depot Multi-Commodity Pickup and Delivery

Published Online:https://doi.org/10.1287/trsc.2024.0720

References

  • Alvarez A, Cordeau JF, Jans R, Munari P, Morabito R (2021) Inventory routing under stochastic supply and demand. Omega 102:102304.CrossrefGoogle Scholar
  • Atakan S, Sen S (2018) A progressive hedging based branch-and-bound algorithm for mixed-integer stochastic programs. Comput. Management Sci. 15(3):501–540.CrossrefGoogle Scholar
  • Bashiri M, Nikzad E, Eberhard A, Hearne J, Oliveira F (2021) A two stage stochastic programming for asset protection routing and a solution algorithm based on the progressive hedging algorithm. Omega 104:102480.CrossrefGoogle Scholar
  • Bent RW, Van Hentenryck P (2004) Scenario-based planning for partially dynamic vehicle routing with stochastic customers. Oper. Res. 52(6):977–987.LinkGoogle Scholar
  • Bertsimas D, Mundru N (2023) Optimization-based scenario reduction for data-driven two-stage stochastic optimization. Oper. Res. 71(4):1343–1361.LinkGoogle Scholar
  • Birge JR, Louveaux F (2011) Introduction to Stochastic Programming, Springer Series in Operations Research and Financial Engineering, 2nd ed. (Springer, New York).CrossrefGoogle Scholar
  • Bosona TG, Gebresenbet G (2011) Cluster building and logistics network integration of local food supply chain. Biosystems Engrg. 108(4):293–302.CrossrefGoogle Scholar
  • Crainic T, Hewitt M, Rei W (2014) Scenario grouping in a progressive hedging-based meta-heuristic for stochastic network design. Comput. Oper. Res. 43:90–99.CrossrefGoogle Scholar
  • Crainic T, Maggioni F, Perboli G, Rei W (2018) Reduced cost-based variable fixing in two-stage stochastic programming. Ann. Oper. Res. 1–37.CrossrefGoogle Scholar
  • Crainic TG, Fu X, Gendreau M, Rei W, Wallace S (2011) Progressive hedging-based meta-heuristics for stochastic network design. Networks 58(2):114–124.CrossrefGoogle Scholar
  • Feillet D (2010) A tutorial on column generation and branch-and-price for vehicle routing problems. 4OR 8(4):407–424.CrossrefGoogle Scholar
  • Gu W, Archetti C, Cattaruzza D, Ogier M, Semet F, Speranza MG (2022) A sequential approach for a multi-commodity two-echelon distribution problem. Computers Indust. Engrg. 163:107793.CrossrefGoogle Scholar
  • Hoogendoorn YN, Spliet R (2023) An improved integer L-shaped method for the vehicle routing problem with stochastic demands. INFORMS J. Comput. 35(2):423–439.LinkGoogle Scholar
  • Hvattum LM, Løkketangen A (2009) Using scenario trees and progressive hedging for stochastic inventory routing problems. J. Heuristics 15(6):527–557.CrossrefGoogle Scholar
  • Kaut M, Wallace SW (2007) Evaluation of scenario-generation methods for stochastic programming. Pacific J. Optim. 3(2):257–271.Google Scholar
  • Keutchayan J, Ortmann J, Rei W (2023) Problem-driven scenario clustering in stochastic optimization. Comput. Management Sci. 20(13).Google Scholar
  • Lanza G, Crainic TG, Rei W, Ricciardi N (2021) Scheduled service network design with quality targets and stochastic travel times. Eur. J. Oper. Res. 288(1):30–46.CrossrefGoogle Scholar
  • Laporte G, Louveaux FV (1993) The integer L-shaped method for stochastic integer programs with complete recourse. Oper. Res. Lett. 13(3):133–142.CrossrefGoogle Scholar
  • Maggioni F, Wallace S (2012) Analyzing the quality of the expected value solution in stochastic programming. Ann. Oper. Res. 200(1):37–57.CrossrefGoogle Scholar
  • Narum BS, Fairbrother J, Wallace SW (2024) Problem-based scenario generation by decomposing output distributions. Eur. J. Oper. Res. 318(1):154–166.CrossrefGoogle Scholar
  • Palacios-Argüello L, Sanchez-Diaz I, Gonzalez-Feliu J, Gondran N (2020) The role of food hubs in enabling local sourcing for school canteens. Aktas E, Bourlakis M, eds. Food Supply Chains in Cities: Modern Tools for Circularity and Sustainability (Springer Palgrave Macmillan, Cham, Switzerland), 233–263.CrossrefGoogle Scholar
  • Prochazka V, Wallace SW (2020) Scenario tree construction driven by heuristic solutions of the optimization problem. Comput. Management Sci. 15(2):277–307.CrossrefGoogle Scholar
  • Rockafellar RT, Wets RJB (1991) Scenario and policy aggregation in optimization under uncertainty. Math. Oper. Res. 16(1):119–147.LinkGoogle Scholar
  • Schmidt-Forth A (2022) Saisonal und regional: So arbeiten Kantinen bio und klimafreundlich. Augsburger Allgemeine. Accessed January 31, 2023, https://www.augsburger-allgemeine.de/geld-leben/augsburg-saisonal-und-regional-so-arbeiten-kantinen-bio-und-klimafreundlich-id63701981.htm.Google Scholar
  • Song Y, Ulmer MW, Thomas BW, Wallace S (2020) Building trust in home services—Stochastic team-orienteering with consistency constraints. Transportation Sci. 54(3):823–838.LinkGoogle Scholar
  • Spliet R, Desaulniers G (2015) The discrete time window assignment vehicle routing problem. Eur. J. Oper. Res. 244(2):379–391.CrossrefGoogle Scholar
  • Truchot D, Andela M (2018) Burnout and hopelessness among farmers: The farmers stressors inventory. Soc. Psychiatry Psychiatric Epidemiology 53(8):859–867.CrossrefGoogle Scholar
  • U.S. Department of Agriculture (2022) USDA expands local foods in school meals through cooperative agreement with Minnesota. Accessed January 31, 2023, https://www.usda.gov/media/press-releases/2022/08/23/usda-expands-local-foods-school-meals-through-cooperative-agreement.Google Scholar
  • Veliz FB, Watson JP, Weintraub A, Wets RJB, Woodruff DL (2015) Stochastic optimization models in forest planning: A progressive hedging solution approach. Ann. Oper. Res. 232:259–274.Google Scholar
  • Zehtabian S, Bastin F (2016) Penalty parameter strategies in progressive hedging algorithm. Technical Report 2016–12, CIRRELT, Montreal.Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.