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Journal of Intelligent Manufacturing

Erschienen in:

19.03.2018

An efficient auction mechanism for regional logistics synchronization

verfasst von: Xianghua Chu, Su Xiu Xu, Fulin Cai, Jiansheng Chen, Quande Qin

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 7/2019

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Abstract

This paper is the first attempt to propose an efficient auction mechanism for the regional logistics synchronization (RLS) problem, which aims to capture both logistics punctuality and simultaneity in a regional logistics network. The main motivation of RLS is motivated by our industrial collaborator, i.e. a third-party logistics (3PL) company, that if the delay has already occurred or will occur, the customers tend to pursue the simultaneity. We develop the one-sided Vickrey–Clarke–Groves (O-VCG) auction to realize incentive compatibility (on the buy side), budget balance, and individual rationality. The vehicle routing problem faced by the 3PL company is formulated as the lane covering problem with RLS requirements. Given the complexity of the proposed model, three canonical swarm intelligence meta-heuristics are employed to address the auction-based RLS problem. Besides, a superior tracking artificial bee colony with novel information learning mechanism is further developed to explore better solutions. Comparison results reveal the effectiveness of the proposed optimizers in terms of realized social welfare. Experimental results show that the O-VCG auction can achieve high synchronization level, approximately allocative efficiency and (ex post) budget balance.

Vorheriger Artikel Constrained dynamic multi-objective evolutionary optimization for operational indices of beneficiation process

Nächster Artikel An effective metaheuristic algorithm for flowshop scheduling with deteriorating jobs

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Titel: An efficient auction mechanism for regional logistics synchronization
verfasst von: Xianghua Chu
Su Xiu Xu
Fulin Cai
Jiansheng Chen
Quande Qin
Publikationsdatum: 19.03.2018
Verlag: Springer US
Erschienen in: Journal of Intelligent Manufacturing / Ausgabe 7/2019
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI: https://doi.org/10.1007/s10845-018-1410-2

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