OR Spectrum

, Volume 32, Issue 3, pp 787–808 | Cite as

Heuristic-based truck scheduling for inland container transportation

Regular Article

Abstract

A truck scheduling problem for container transportation in a local area with multiple depots and multiple terminals including containers as a resource for transportation is addressed. Four types of movements of containers as inbound full, outbound full, inbound empty and outbound empty movements as well as the time windows at both the origin and the destination are considered. The total operating time of all trucks in operation is taken as the optimization criterion that has to be minimized. The problem is mathematically modeled based on a preparative graph formulation and falls into an extension of the multiple traveling salesman problem with time windows (m-TSPTW). The window partition based solution method for the m-TSPTW in Wang and Regan (Transp Res Part B: Methodol 36:97–112, 2002) is modified so that its computation time is reduced greatly. The experiments based on a number of randomly generated instances indicate that the modified method is quite fast and the quality of solutions is relatively high for the m-TSPTW. These experiments also demonstrate that our approach is able to generate high-quality results for the equivalent truck scheduling and inland container movement problem in container drayage operations.

Keywords

Container transportation Traveling salesman problem (TSP) Time window Heuristics Container drayage operation Container as a resource in transportation planning 

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References

  1. Appelgren LH (1969) A column generation approach for a ship scheduling problem. Transp Sci 3: 53–68CrossRefGoogle Scholar
  2. Appelgren LH (1971) Integer programming methods for a vessel scheduling problem. Transp Sci 5: 62–74Google Scholar
  3. Battiti R, Tecchiolli G (1994) The reactive tabu search. ORSA J Comput 6: 126–140Google Scholar
  4. Bektas T (2006) The multiple traveling salesman problem: an overview of formulations and solution procedures. Omega 34: 209–219CrossRefGoogle Scholar
  5. Caris A, Janssens GK (2009) A local search heuristic for the pre- and end- haulage of intermodal container terminals. Comput Oper Res 36: 2763–2772CrossRefGoogle Scholar
  6. Cheung RK, Shi N, Powell WB, Simao HP (2008) An attribute-decision model for cross-border drayage problem. Transp Res Part E: Logist Transp Rev 44: 217–234CrossRefGoogle Scholar
  7. Chung KH, Ko CS, Shin JY, Hwang H, Kim KH (2007) Development of mathematical models for the container road transportation in Korean trucking industries. Comput Ind Eng 53: 252–262CrossRefGoogle Scholar
  8. Coslovich L, Pesenti R, Ukovich W (2006) Minimizing fleet operating costs for a container transportation company. Eur J Oper Res 171: 776–786CrossRefGoogle Scholar
  9. Günther H-O, Kim K-H (2006) Container terminals and terminal operations. OR Spectr 28: 437–445CrossRefGoogle Scholar
  10. Ileri Y (2006) Drayage optimization in truck/rail networks. PhD thesis, Georgia Institute of TechnologyGoogle Scholar
  11. Imai A, Nishimura E, Current J (2007) A Lagrangian relaxation-based heuristic for the vehicle routing with full container load. Eur J Oper Res 176: 87–105CrossRefGoogle Scholar
  12. Jula H, Dessouky M, Ioannou P, Chassiakos A (2005) Container movement by trucks in metropolitan networks: modeling and optimization. Transp Res Part E: Logist Transp Rev 41: 235–259CrossRefGoogle Scholar
  13. Levin A (1971) Scheduling and fleet routing models for transportation systems. Transp Sci 5: 232–255CrossRefGoogle Scholar
  14. Macharis C, Bontekoning YM (2004) Opportunities for OR in intermodal freight transport research: a review. Eur J Oper Res 153: 400–416CrossRefGoogle Scholar
  15. Namboothiri R (2006) Planning container drayage operations at congested seaports. PhD thesis, Georgia Institute of TechnologyGoogle Scholar
  16. Namboothiri R, Erera AL (2008) Planning local container drayage operations given a port access appointment system. Transp Res Part E: Logist Transp Rev 44: 185–202Google Scholar
  17. Pisinger D, Ropke S (2007) A general heuristic for vehicle routing problems. Comput Oper Res 34: 2403–2435CrossRefGoogle Scholar
  18. Stahlbock R, Voß S (2008) Operations research at container terminals: a literature update. OR Spectr 30: 1–52CrossRefGoogle Scholar
  19. Tjokroamidjojo D, Kutanoglu E, Taylor GD (2006) Quantifying the value of advance load information in truckload trucking. Transp Res Part E 42: 340–357CrossRefGoogle Scholar
  20. Toth P, Vigo D (2002) The vehicle routing problem. SIAM (Society for Industrial and Applied Mathematics), PhiladelphiaGoogle Scholar
  21. Wang X, Regan AC (2002) Local truckload pickup and delivery with hard time window constraints. Transp Res Part B: Methodol 36: 97–112CrossRefGoogle Scholar
  22. Wen S, Zhou P (2007) A container vehicle routing model with variable traveling time. In: IEEE international conference on automation and logistics, 2007, pp 2243–2247Google Scholar
  23. Zhang RY, Yun WY (2008) An optimum route modeling for container truck transportation. In: Asia conference on intelligent manufacturing & logistics systems, Kitakyushu, Japan, pp 356–362Google Scholar
  24. Zhang RY, Yun WY, Moon I (2009) A reactive tabu search algorithm for the multi-depot container truck transportation problem. Transp Res Part E 45: 904–914CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Institute of Systems EngineeringNortheastern UniversityShenyangChina
  2. 2.Department of Industrial EngineeringPusan National UniversityBusanKorea
  3. 3.Faculty of Business Studies and EconomicsChair of Logistics, University of BremenBremenGermany

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