Service-Oriented Considerate Routing: Data, Predictions, and Robust Decisions

Published Online:https://doi.org/10.1287/mnsc.2024.05530

References

  • Adulyasak Y, Cordeau JF, Jans R (2015) Benders decomposition for production routing under demand uncertainty. Oper. Res. 63(4):851–867.LinkGoogle Scholar
  • Agra A, Christiansen M, Figueiredo R, Hvattum LM, Poss M, Requejo C (2013) The robust vehicle routing problem with time windows. Comput. Oper. Res. 40(3):856–866.CrossrefGoogle Scholar
  • Azi N, Gendreau M, Potvin JY (2014) An adaptive large neighborhood search for a vehicle routing problem with multiple routes. Comput. Oper. Res. 41:167–173.CrossrefGoogle Scholar
  • Baldacci R, Toth P, Vigo D (2010) Exact algorithms for routing problems under vehicle capacity constraints. Ann. Oper. Res. 175:213–245.CrossrefGoogle Scholar
  • Beardwood J, Halton JH, Hammersley JM (1959) The shortest path through many points. Math. Proc. Cambridge Philos. Soc. 55(4):299–327.CrossrefGoogle Scholar
  • Bertsimas D, Brown DB, Caramanis C (2011) Theory and applications of robust optimization. SIAM Rev. 53(3):464–501.CrossrefGoogle Scholar
  • Carlsson JG, Liu S, Salari N, Yu H (2024) Provably good region partitioning for on-time last-mile delivery. Oper. Res. 72(1):91–109.LinkGoogle Scholar
  • Cheng C, Sim M, Zhao Y (2024) Robust workforce management with crowdsourced delivery. Oper. Res. 73(2):595–612.LinkGoogle Scholar
  • Cordeau JF, Laporte G, Mercier A (2001) A unified tabu search heuristic for vehicle routing problems with time windows. J. Oper. Res. Soc. 52(8):928–936.CrossrefGoogle Scholar
  • Dantzig GB, Ramser JH (1959) The truck dispatching problem. Management Sci. 6(1):80–91.LinkGoogle Scholar
  • Delage E, Ye Y (2010) Distributionally robust optimization under moment uncertainty with application to data-driven problems. Oper. Res. 58(3):595–612.LinkGoogle Scholar
  • Desaulniers G (2010) Branch-and-price-and-cut for the split-delivery vehicle routing problem with time windows. Oper. Res. 58(1):179–192.LinkGoogle Scholar
  • Dieter P, Caron M, Schryen G (2023) Integrating driver behavior into last-mile delivery routing: Combining machine learning and optimization in a hybrid decision support framework. Eur. J. Oper. Res. 311(1):283–300.CrossrefGoogle Scholar
  • Dietvorst BJ, Simmons JP, Massey C (2018) Overcoming algorithm aversion: People will use imperfect algorithms if they can (even slightly) modify them. Management Sci. 64(3):1155–1170.LinkGoogle Scholar
  • Fatehi S, Wagner MR (2022) Crowdsourcing last-mile deliveries. Manufacturing Service Oper. Management 24(2):791–809.LinkGoogle Scholar
  • Fu G, Zhang P, Lei D, Qi W, Shen ZJM (2023) Learning for guiding: A framework for unlocking trust and improving performance in last-mile delivery. Preprint, submitted November 30, https://doi.org/10.2139/ssrn.4639706.Google Scholar
  • Gao R, Kleywegt A (2023) Distributionally robust stochastic optimization with Wasserstein distance. Math. Oper. Res. 48(2):603–655.LinkGoogle Scholar
  • Golden BL, Magnanti TL, Nguyen HQ (1977) Implementing vehicle routing algorithms. Networks 7(2):113–148.CrossrefGoogle Scholar
  • He L, Liu S, Shen ZJM (2022) Smart urban transport and logistics: A business analytics perspective. Production Oper. Management 31(10):3771–3787.CrossrefGoogle Scholar
  • Jaillet P, Qi J, Sim M (2016) Routing optimization under uncertainty. Oper. Res. 64(1):186–200.LinkGoogle Scholar
  • Johnson DS, McGeoch LA, Rothberg EE (1996) Asymptotic experimental analysis for the Held-Karp traveling salesman bound. SODA’96: Proc. Seventh Annual ACM-SIAM Sympos. Discrete Algorithms (Society for Industrial and Applied Mathematics, Philadelphia), 341–350.Google Scholar
  • Lee C, Lee K, Park S (2012) Robust vehicle routing problem with deadlines and travel time/demand uncertainty. J. Oper. Res. Soc. 63(9):1294–1306.CrossrefGoogle Scholar
  • Li X, Tan Y, Xue D (2022) From world factory to global city-region: The dynamics of manufacturing in the Pearl River delta and its spatial pattern in the 21st century. Land 11(5):625.CrossrefGoogle Scholar
  • Lim SFWT (2023) Why so many packages don’t get delivered. Harvard Bus. Rev. (November 28), https://hbr.org/2023/11/research-why-so-many-packages-dont-get-delivered.Google Scholar
  • Lim K, Ong J (2022) Food delivery riders and the road: Accidents, safety and the rush to complete orders. Faced with fatigue and rush to meet orders, food delivery riders grapple daily with road safety risks. (July 18), https://www.channelnewsasia.com/today/big-read/food-delivery-riders-road-accidents-safety-rush-orders-big-read-2815206.Google Scholar
  • Lim SFWT, Wang Q, Webster S (2023) Do it right the first time: Vehicle routing with home delivery attempt predictors. Production Oper. Management 32(4):1262–1284.CrossrefGoogle Scholar
  • Liu S, Luo Z (2023) On-demand delivery from stores: Dynamic dispatching and routing with random demand. Manufacturing Service Oper. Management 25(2):595–612.LinkGoogle Scholar
  • Liu S, He L, Max Shen ZJ (2021) On-time last-mile delivery: Order assignment with travel-time predictors. Management Sci. 67(7):4095–4119.LinkGoogle Scholar
  • Long DZ, Sim M, Zhou M (2023) Robust satisficing. Oper. Res. 71(1):61–82.LinkGoogle Scholar
  • Lysgaard J, Letchford AN, Eglese RW (2004) A new branch-and-cut algorithm for the capacitated vehicle routing problem. Math. Programming 100:423–445.CrossrefGoogle Scholar
  • Mao W, Ming L, Rong Y, Tang CS, Zheng H (2025) Faster deliveries and smarter order assignments for an on-demand meal delivery platform. J. Oper. Management 71(2):220–245.Google Scholar
  • Mohajerin Esfahani P, Kuhn D (2018) Data-driven distributionally robust optimization using the Wasserstein metric: Performance guarantees and tractable reformulations. Math. Programming 171(1–2):115–166.CrossrefGoogle Scholar
  • Özarık SS, da Costa P, Florio AM (2024) Machine learning for data-driven last-mile delivery optimization. Transportation Sci. 58(1):27–44.LinkGoogle Scholar
  • Penna PHV, Subramanian A, Ochi LS, Vidal T, Prins C (2019) A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet. Ann. Oper. Res. 273:5–74.CrossrefGoogle Scholar
  • Stroh AM, Erera AL, Toriello A (2022) Tactical design of same-day delivery systems. Management Sci. 68(5):3444–3463.LinkGoogle Scholar
  • Tashman LJ (2000) Out-of-sample tests of forecasting accuracy: An analysis and review. Internat. J. Forecasting 16(4):437–450.CrossrefGoogle Scholar
  • Toth P, Vigo D (2002) The Vehicle Routing Problem (Society for Industrial and Applied Mathematics, Philadelphia).CrossrefGoogle Scholar
  • Uzir MUH, Al Halbusi H, Thurasamy R, Hock RLT, Aljaberi MA, Hasan N, Hamid M (2021) The effects of service quality, perceived value and trust in home delivery service personnel on customer satisfaction: Evidence from a developing country. J. Retailing Consumer Services 63:102721.CrossrefGoogle Scholar
  • Vidal T, Laporte G, Matl P (2020) A concise guide to existing and emerging vehicle routing problem variants. Eur. J. Oper. Res. 286(2):401–416.CrossrefGoogle Scholar
  • Wiesemann W, Kuhn D, Sim M (2014) Distributionally robust convex optimization. Oper. Res. 62(6):1358–1376.LinkGoogle Scholar
  • Zhang Y, Zhang Z, Lim A, Sim M (2021) Robust data-driven vehicle routing with time windows. Oper. Res. 69(2):469–485.LinkGoogle 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.