On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services
AbstractIn 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 . 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
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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.
Sun Y, Lang M, Wang J. On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services. Information. 2016; 7(1):13.Chicago/Turabian Style
Sun, Yan; Lang, Maoxiang; Wang, Jiaxi. 2016. "On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services." Information 7, no. 1: 13.
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