A benders decomposition algorithm for a bid generation problem in the procurement of Three-echelon transportation services

被引:1
|
作者
Lyu, Xiaohui [1 ]
Chen, Haoxun [2 ]
Wang, Nengmin [3 ,4 ]
Yang, Zhen [3 ,4 ]
机构
[1] Soochow Univ, Sch Polit & Publ Adm, 199 Renai Rd,Suzhou Ind Pk, Suzhou 215123, Jiangsu, Peoples R China
[2] Univ Technol Troyes, Lab Comp Sci & Digital Soc LIST3N, Logist & Optimizat Ind Syst, 12 Rue Marie Curie,CS 42060, F-10004 Troyes, France
[3] Xi An Jiao Tong Univ, Sch Management, 28 Xianning Rd, Xian 710049, Shaanxi, Peoples R China
[4] ERC Proc Min Mfg Serv Shaanxi Prov, 28 Xianning Rd, Xian 710049, Shaanxi, Peoples R China
基金
国家自然科学基金重大项目; 中国国家自然科学基金;
关键词
Transportation service procurement; Combinatorial auction; Bid generation problem; Three -echelon transportation; Benders decomposition; VEHICLE-ROUTING PROBLEM; LARGE NEIGHBORHOOD SEARCH; CUT ALGORITHM; AUCTIONS;
D O I
10.1016/j.cor.2023.106291
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we address a bid generation problem in a combinatorial auction for the procurement of transportation services with time windows in a three-echelon transportation network. By considering the interconnectivity of transportation operations in different echelons, a path-based mathematical programming model is proposed for this problem. To solve the model with complicated linking constraints, a Benders decomposition algorithm in a heuristic manner is designed. The algorithm iteratively and alternatively solves a master problem that is a selective routing problem with time windows for the second echelon and two subproblems that are routing problems with time windows for the first and third echelon respectively. The basic Benders decomposition algorithm is enhanced by applying the acceleration techniques of multiple cuts, Pareto-optimal cuts and multiple cuts combined with Pareto-optimal cuts. Extensive computational experiments were performed to evaluate the effectiveness of the acceleration techniques and the efficiency of the algorithm. The computational results indicate that the enhanced algorithm significantly outperforms CPLEX in terms of solution quality and CPU time. Moreover, our sensitivity analysis on some key parameters of the model show that the lower the proportion of reserved requests, the larger of the capacity of each vehicle, and the higher the percentage of profit increase of a carrier after bidding.
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页数:20
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