A bid generation problem for combinatorial transportation auctions considering in-vehicle consolidations. Issue 2 (7th July 2020)

• Record Type: Journal Article
• Authors: Yan, Fang; Chen, Kai; Xu, Manjing
• Is Part Of: Asia Pacific journal of marketing and logistics. Volume 33:Issue 2(2021)
• Page Start: 491
• Page End: 512
• Publication Date: 2020-07-07
• Subjects: Combinatorial transportation auctions -- In-vehicle consolidations -- Synergy-based approach -- Particle swarm optimization; Marketing -- Asia -- Periodicals; Marketing -- Pacific Area -- Periodicals; Business logistics -- Asia -- Periodicals; Business logistics -- Pacific Area -- Periodicals; Consumer behavior -- Asia -- Periodicals; Consumer behavior -- Pacific Area -- Periodicals; 381.095
• DOI: 10.1108/APJML-09-2019-0556
• Languages: English
• ISSNs: 1355-5855

Abstract

Abstract : Purpose: This paper studied a bid generation problem in combinatorial transportation auctions that considered in-vehicle consolidations. The purpose of this paper seeks to establish mixed integer programming to the most profitable transportation task packages. Design/methodology/approach: The authors proposes a mathematical model to identify the most profitable transportation task packages under vehicle capacity, flow balance and in-vehicle consolidation operational constraints, after which a two-phase heuristic algorithm was designed to solve the proposed model. In the first phase, a method was defined to compute bundle synergy, which was then combined with particle swarm optimization (PSO) to determine a satisfactory task package, and in the second phase, the PSO was adopted to program vehicle routings that considered in-vehicle consolidation. Findings: Three numerical examples were given to analyze the effects of the proposed model and method, with the first two small-scale examples coming from the same data base and the third being a larger scale example. The results showed that: (1) the proposed model was able to find a satisfactory solution for the three numerical examples; (2) the computation time was significantly shorter than the accurate algorithm and (3) considering in-vehicle consolidations operations could increase the carrier profits. Originality/value: The highlights of this paper are summarized as following: (1) it considers in-vehicle consolidation when generating bids to maximize profits; (2) it simultaneously identifies the most valuable lane packages and reconstructs vehicle routes and (3) proposes a simple but effective synergy-based method to solve the model.