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Information 2016, 7(1), 13; doi:10.3390/info7010013

On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services

1
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2
MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 7 January 2016 / Revised: 16 February 2016 / Accepted: 29 February 2016 / Published: 4 March 2016
(This article belongs to the Section Information Processes)
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Abstract

In this study, we combine the fuzzy customer information problem with the multicommodity multimodal routing with schedule-based services which was explored in our previous study [1]. The fuzzy characteristics of the customer information are embodied in the demanded volumes of the multiple commodities and the time windows of their due dates. When the schedule-based services are considered in the routing, schedule constraints emerge because the operations of block container trains should follow their predetermined schedules. This will restrict the routes selection from space-time feasibility. To solve this combinatorial optimization problem, we first build a fuzzy chance-constrained nonlinear programming model based on fuzzy possibility theory. We then use a crisp equivalent method and a linearization method to transform the proposed model into the classical linear programming model that can be effectively solved by the standard mathematical programming software. Finally, a numerical case is presented to demonstrate the feasibility of the proposed method. The sensitivity of the best solution with respect to the values of the confidence levels is also examined. View Full-Text
Keywords: multicommodity; multimodal routing; fuzzy demanded volume; fuzzy soft time window; fuzzy chance-constrained programming multicommodity; multimodal routing; fuzzy demanded volume; fuzzy soft time window; fuzzy chance-constrained programming
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sun, Y.; Lang, M.; Wang, J. On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services. Information 2016, 7, 13.

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