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• W2292610231 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." @default.
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• W2292610231 date "2016-03-04" @default.
• W2292610231 modified "2023-09-26" @default.
• W2292610231 title "On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services" @default.
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• W2292610231 doi "https://doi.org/10.3390/info7010013" @default.
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