Stochastic Network Design for Planning Scheduled Transportation Services: The Value of Deterministic Solutions

Published Online:https://doi.org/10.1287/ijoc.2018.0819

References

  • Andersen J, Crainic TG, Christiansen M (2009a) Service network design with asset management: Formulations and comparative analyses. Transportation Res. Part C: Emerging Tech. 17(2):197–207.CrossrefGoogle Scholar
  • Andersen J, Crainic TG, Christiansen M (2009b) Service network design with management and coordination of multiple fleets. Eur. J. Oper. Res. 193(2):377–389.CrossrefGoogle Scholar
  • Andersen J, Christiansen M, Crainic TG, Grønhaug R (2011) Branch and price for service network design with asset management constraints. Transportation Sci. 45(1):33–49.LinkGoogle Scholar
  • Armacost AP, Barnhart C, Ware KA (2002) Composite variable formulations for express shipment service network design. Transportation Sci. 36(1):1–20.LinkGoogle Scholar
  • Bai R, Wallace SW, Li J, Chong AYL (2014) Stochastic service network design with rerouting. Transportation Res. Part B: Methodological 60(February):50–65.CrossrefGoogle Scholar
  • Barnhart C, Schneur RR (1996) Air network design for express shipment service. Oper. Res. 44(6):852–863.LinkGoogle Scholar
  • Birge JR (1982) The value of the stochastic solution in stochastic linear programs with fixed recourse. Math. Programming 24(1):314–325.CrossrefGoogle Scholar
  • Büdenbender K, Grünert T, Sebastian H-J (2000) A hybrid tabu search/branch-and-bound algorithm for the direct flight network design problem. Transportation Sci. 34(4):364–380.LinkGoogle Scholar
  • Christiansen M, Fagerholt K, Ronen D (2004) Ship routing and scheduling: Status and perspectives. Transportation Sci. 38(1):1–18.LinkGoogle Scholar
  • Christiansen M, Fagerholt K, Nygreen B, Ronen D (2007) Barnhart C, Laporte G, eds. Handbooks in Operations Research and Management Science. Maritime Transportation, Vol. 14 (Elsevier, Amsterdam), 189–284.Google Scholar
  • Christiansen M, Fagerholt K, Nygreen B, Ronen D (2013) Ship routing and scheduling in the new millennium. Eur. J. Oper. Res. 228(3):467–483.CrossrefGoogle Scholar
  • Cordeau J-F, Toth P, Vigo D (1998) A survey of optimization models for train routing and scheduling. Transportation Sci. 32(4):380–404.LinkGoogle Scholar
  • Crainic TG (2000) Service network design in freight transportation. Eur. J. Oper. Res. 122(2):272–288.CrossrefGoogle Scholar
  • Crainic TG (2003) Long-haul freight transportation. Hall RW, ed. Handbook of Transportation Science, 2nd ed. (Kluwer Academic Publishers, Boston), 451–516.CrossrefGoogle Scholar
  • Crainic TG, Kim KH (2007) Barnhart C, Laporte G, eds. Transportation, Handbooks in Operations Research and Management Science. Chap. 8 Intermodal Transportation, Vol. 14 (North-Holland, Amsterdam).Google Scholar
  • Crainic TG, Laporte G (1997) Planning models for freight transportation. Eur. J. Oper. Res. 97(3):409–438.CrossrefGoogle Scholar
  • Crainic TG, Rousseau JM (1986) Multicommodity, multimode freight transportation: A general modeling and algorithmic framework for the service network design problem. Transportation Res. Part B: Methodological 20(3):225–242.CrossrefGoogle Scholar
  • Crainic TG, Roy J (1988) OR tools for tactical freight transportation planning. Eur. J. Oper. Res. 33(3):290–297.CrossrefGoogle Scholar
  • Crainic TG, Dejax P, Delorme L (1989) Models for multimode multicommodity location problems with interdepot balancing requirements. Ann. Oper. Res. 18(1):277–302.CrossrefGoogle Scholar
  • Crainic T, Ferland J-A, Rousseau J-M (1984) A tactical planning model for rail freight transportation. Transportation Sci. 18(2):165–184.LinkGoogle Scholar
  • Crainic TG, Fu X, Gendreau M, Rei W, Wallace SW (2011) Progressive hedging-based metaheuristics for stochastic network design. Networks 58(2):114–124.CrossrefGoogle Scholar
  • Dejax PJ, Crainic TG (1987) A review of empty flows and fleet management models in freight transportation. Transportation Sci. 21(4):227–248.LinkGoogle Scholar
  • Delorme L, Roy J, Rousseau JM (1988) Motor-carriers operations planning models: A state of the art. Bianco L, Bella AL, eds. Freight Transport Planning and Logistics (Springer-Verlag, Berlin), 510–545.CrossrefGoogle Scholar
  • Farvolden JM, Powell WB (1991) A dynamic network model for less-than-truckload motor carrier operations. Working Paper 90-05, Department of Industrial Engineering, University of Toronto.Google Scholar
  • Farvolden JM, Powell WB (1994) Subgradient methods for the service network design problem. Transportation Sci. 28(3):256–272.LinkGoogle Scholar
  • Farvolden JM, Powell WB, Lustig IJ (1993) A primal partitioning solution for the arc-chain formulation of a multicommodity network flow problem. Oper. Res. 41(4):669–693.LinkGoogle Scholar
  • Gorman MF (1998a) An application of genetic and tabu searches to the freight railroad operating plan problem. Ann. Oper. Res. 78(January):51–69.CrossrefGoogle Scholar
  • Gorman MF (1998b) Santa Fe railway uses an operating-plan model to improve its service design. Interfaces 28(4):1–12.LinkGoogle Scholar
  • Grünert T, Sebastian HJ (2000) Planning models for long-haul operations of postal and express shipment companies. Eur. J. Oper. Res. 122(2):289–309.CrossrefGoogle Scholar
  • Grünert T, Sebastian HJ, Tharigen M (1999) The design of a letter-mail transportation network by intelligent techniques. Sprague R, ed. Proc. 32nd Ann. Hawaii Internat. Conf. Systems Sci., HICSS-32 (IEEE Computer Society, Washington, DC), 16.Google Scholar
  • Haghani AE (1989) Formulation and solution of a combined train routing and makeup, and empty car distribution model. Transportation Res. Part B: Methodological 23(6):433–452.CrossrefGoogle Scholar
  • Higle JL, Wallace SW (2003) Sensitivity analysis and uncertainty in linear programming. Interfaces 33(4):53–60.LinkGoogle Scholar
  • Hoff A, Lium AG, Løkketangen A, Crainic TG (2010) A metaheuristic for stochastic service network design. J. Heuristics 16(5):653–679.CrossrefGoogle Scholar
  • Høyland K, Kaut M, Wallace SW (2003) A heuristic for moment-matching scenario generation. Comput. Optim. Appl. 24(2/3):169–185.CrossrefGoogle Scholar
  • Kall P, Wallace SW (1994) Stochastic Programming, 2nd ed. (John Wiley & Sons, Chichester, UK).Google Scholar
  • Kaut M, Wallace SW (2007) Evaluation of scenario-generation methods for stochastic programming. Pacific J. Optim. 3(2):257–271.Google Scholar
  • Keaton MH (1989) Designing optimal railroad operating plans: Lagrangian relaxation and heuristic approaches. Transportation Res. Part B: Methodological 23(6):415–431.CrossrefGoogle Scholar
  • Keaton MH (1991) Service-cost trade-offs for carload freight traffic in the U.S. rail industry. Transportation Res. Part A: General 25(6):363–374.CrossrefGoogle Scholar
  • Keaton MH (1992) Designing railroad operating plans: A dual adjustment method for implementing Lagrangian relaxation. Transportation Sci. 26(4):263–279.LinkGoogle Scholar
  • Kim D, Barnhart C, Ware K, Reinhardt G (1999) Multimodal express package delivery: A service network design application. Transportation Sci. 33(4):391–407.LinkGoogle Scholar
  • King AJ, Wallace SW (2012) Modeling with Stochastic Programming. Springer Series in Operations Research and Financial Engineering (Springer, New York).CrossrefGoogle Scholar
  • Lamar BW, Sheffi Y, Powell WB (1990) A capacity improvement lower bound for fixed charge network design problems. Oper. Res. 38(4):704–710.LinkGoogle Scholar
  • Lium AG, Crainic TG, Wallace SW (2007) Correlations in stochastic programming: A case from stochastic service network design. Asia-Pacific J. Oper. Res. 24(02):161–179.CrossrefGoogle Scholar
  • Lium A-G, Crainic TG, Wallace SW (2009) A study of demand stochasticity in service network design. Transportation Sci. 43(2):144–157.LinkGoogle Scholar
  • Maggioni F, Wallace SW (2012) Analyzing the quality of the expected value solution in stochastic programming. Ann. Oper. Res. 200(1):37–54.CrossrefGoogle Scholar
  • Newton HN, Barnhart C, Vance PH (1998) Constructing railroad blocking plans to minimize handling costs. Transportation Sci. 32(4):330–345.LinkGoogle Scholar
  • Pedersen MB, Crainic TG, Madsen OBG (2009) Models and tabu search metaheuristics for service network design with asset-balance requirements. Transportation Sci. 43(2):158–177.LinkGoogle Scholar
  • Powell WB (1986) A local improvement heuristic for the design of less-than-truckload motor carrier networks. Transportation Sci. 20(4):246–257.LinkGoogle Scholar
  • Powell WB, Sheffi Y (1983) The load planning problem of motor carriers: Problem description and a proposed solution approach. Transportation Res. Part A: General 17(6):471–480.CrossrefGoogle Scholar
  • Powell WB, Sheffi Y (1986) Interactive optimization for motor carrier load planning. J. Bus. Logist. 7(2):64–90.Google Scholar
  • Powell WB, Sheffi Y (1989) Design and implementation of an interactive optimization system for network design in the motor carrier industry. Oper. Res. 37(1):12–29.LinkGoogle Scholar
  • Roy J, Delorme L (1989) Netplan: A network optimization model for tactical planning in the less-than-truckload motor-carrier industry. INFOR: Inform. Systems Oper. Res. 27(1):22–35.CrossrefGoogle Scholar
  • Sharypova K, Crainic TG, van Woensel T, Fransoo JC (2012) Scheduled service network design with synchronization and transshipment constraints for intermodal container transportation networks. Technical Report CIRRELT-2012-77, Centre interuniversitaire de recherche sur les réseaux d’entreprise, la logistique et le transport, Montréal, QC, Canada.Google Scholar
  • Smilowitz KR, Atamtürk A, Daganzo CF (2003) Deferred item and vehicle routing within integrated networks. Transportation Res. Part E: Logist. Transportation Rev. 39(4):305–323.CrossrefGoogle Scholar
  • Thapalia BK, Crainic TG, Kaut M, Wallace SW (2011) Single-commodity stochastic network design with multiple sources and sinks. INFOR: Inform. Systems Oper. Res. 49(3):193–211.CrossrefGoogle Scholar
  • Thapalia BK, Crainic TG, Kaut M, Wallace SW (2012a) Single-commodity network design with random edge capacities. Eur. J. Oper. Res. 220(2):394–403.CrossrefGoogle Scholar
  • Thapalia BK, Wallace SW, Kaut M, Crainic TG (2012b) Single source single-commodity stochastic network design. Comput. Management Sci. 9(1):139–160.CrossrefGoogle Scholar
  • Wallace SW (2000) Decision making under uncertainty: Is sensitivity analysis of any use? Oper. Res. 48(1):20–25.LinkGoogle Scholar
  • Wang X, Wallace SW (2016) Stochastic scheduled service network design in the presence of a spot market for excess capacity. EURO J. Transportation Logist. 5(4):393–413.CrossrefGoogle Scholar
  • Zhu E, Crainic TG, Gendreau M (2014) Scheduled service network design for freight rail transportation. Oper. Res. 62(2):383–400.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.