On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services
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 commoditie...
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| Format: | Article |
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MDPI AG
2016-03-01
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| Online Access: | http://www.mdpi.com/2078-2489/7/1/13 |
| _version_ | 1818541074097897472 |
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| author | Yan Sun Maoxiang Lang Jiaxi Wang |
| author_facet | Yan Sun Maoxiang Lang Jiaxi Wang |
| author_sort | Yan Sun |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-11T22:03:47Z |
| format | Article |
| id | doaj.art-d74397e97bc6431eb9a49143e76fc7b1 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-12-11T22:03:47Z |
| publishDate | 2016-03-01 |
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| spelling | doaj.art-d74397e97bc6431eb9a49143e76fc7b12022-12-22T00:49:02ZengMDPI AGInformation2078-24892016-03-01711310.3390/info7010013info7010013On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based ServicesYan Sun0Maoxiang Lang1Jiaxi Wang2School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaIn 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.http://www.mdpi.com/2078-2489/7/1/13multicommoditymultimodal routingfuzzy demanded volumefuzzy soft time windowfuzzy chance-constrained programming |
| spellingShingle | Yan Sun Maoxiang Lang Jiaxi Wang On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services Information multicommodity multimodal routing fuzzy demanded volume fuzzy soft time window fuzzy chance-constrained programming |
| title | On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services |
| title_full | On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services |
| title_fullStr | On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services |
| title_full_unstemmed | On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services |
| title_short | On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services |
| title_sort | on solving the fuzzy customer information problem in multicommodity multimodal routing with schedule based services |
| topic | multicommodity multimodal routing fuzzy demanded volume fuzzy soft time window fuzzy chance-constrained programming |
| url | http://www.mdpi.com/2078-2489/7/1/13 |
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