Decision Support for Collaboration of Carriers Based on Clustering, Swarm Intelligence and Shapley Value

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Decision Support System Technology Pub Date : 2020-01-01 DOI:10.4018/ijdsst.2020010102
Fu-Shiung Hsieh
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引用次数: 3

Abstract

Transportation costs constitute an important part in providing services and goods to customers. How to reduce transportation costs has a significant influence on competitive advantage of carriers. Although a lot of vehicle routing problems (VRP) and their variants have been extensively studied to reduce transportation costs via optimization of vehicle routes, little research focuses on how to achieve lower transportation costs through cooperation of carriers while fulfilling customer requests. This article aims to develop a decision support framework to facilitate cooperation of carriers to reduce transportation costs further based on information sharing, clustering requests, swarm intelligence, and the Shapley value cost allocation scheme. Two decision models for two carriers are compared: one reflecting the scenario without cooperation between the two carriers and the other one reflecting the scenario with cooperation between the two carriers. The simulation results indicate that the swarm intelligence and Shapley value based cooperative decision model outperforms that of the independent decision model.
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基于聚类、群智能和Shapley值的运营商协作决策支持
运输成本是向客户提供服务和货物的重要组成部分。如何降低运输成本对承运人的竞争优势有着重要的影响。为了通过优化车辆路线来降低运输成本,人们对车辆路线问题及其变体进行了大量的研究,但如何在满足客户需求的同时,通过承运人的合作来降低运输成本的研究却很少。本文旨在基于信息共享、聚类请求、群体智能和Shapley价值成本分配方案,开发一个促进承运人合作进一步降低运输成本的决策支持框架。比较了两家运营商的两种决策模型:一种反映了两家运营商不合作的情景,另一种反映了两家运营商合作的情景。仿真结果表明,基于群体智能和Shapley值的协同决策模型优于独立决策模型。
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来源期刊
International Journal of Decision Support System Technology
International Journal of Decision Support System Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.20
自引率
18.20%
发文量
40
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