Two-phase heuristic algorithms for full truckloads multi-depot capacitated vehicle routing problem in carrier collaboration

  • Authors:

  • Ran Liu;Zhibin Jiang;Richard Y. K. Fung;Feng Chen;Xiao Liu

  • Affiliations:

  • Department of Industrial Engineering and Logistics Management, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Rd., Shanghai 200240, PR China;Department of Industrial Engineering and Logistics Management, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Rd., Shanghai 200240, PR China;Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong;Department of Industrial Engineering and Logistics Management, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Rd., Shanghai 200240, PR China;Department of Industrial Engineering and Logistics Management, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Rd., Shanghai 200240, PR China

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2010

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Abstract

Collaborative transportation, as an emerging new mode, represents one of the major developing trends of transportation systems. Focusing on the full truckloads multi-depot capacitated vehicle routing problem in carrier collaboration, this paper proposes a mathematical programming model and its corresponding graph theory model, with the objective of minimizing empty vehicle movements. A two-phase greedy algorithm is given to solve practical large-scale problems. In the first phase, a set of directed cycles is created to fulfil the transportation orders. In the second phase, chains that are composed of cycles are generated. Furthermore, a set of local search strategies is put forward to improve the initial results. To evaluate the performance of the proposed algorithms, two lower bounds are developed. Finally, computational experiments on various randomly generated problems are conducted. The results show that the proposed methods are effective and the algorithms can provide reasonable solutions within an acceptable computational time.