Fuzzy multi-objective chance-constrained programming model for hazardous materials transportation

Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy multi-objective programming model that minimizes the transportation risk to life, travel time and fuel consumption. First, we present the risk model, trave...

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Veröffentlicht in:International journal of general systems Jg. 45; H. 3; S. 286 - 310
Hauptverfasser: Du, Jiaoman, Yu, Lean, Li, Xiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Abingdon Taylor & Francis 02.04.2016
Taylor & Francis LLC
Schlagworte:
Algorithms
Federal regulation
Fuel consumption
Fuzzy
fuzzy chance-constrained programming
Fuzzy logic
Goal programming
Hazardous materials
Hazardous materials transportation
hybrid intelligent algorithm
Mathematical models
multi-objective programming
Programming
Risk
Transportation
ISSN:0308-1079, 1563-5104
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Zusammenfassung:Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy multi-objective programming model that minimizes the transportation risk to life, travel time and fuel consumption. First, we present the risk model, travel time model and fuel consumption model. Furthermore, we formulate a chance-constrained programming model within the framework of credibility theory, in which the lengths of arcs in the transportation network are assumed to be fuzzy variables. A hybrid intelligent algorithm integrating fuzzy simulation and genetic algorithm is designed for finding a satisfactory solution. Finally, some numerical examples are given to demonstrate the efficiency of the proposed model and algorithm.
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ISSN:0308-1079
1563-5104
DOI:10.1080/03081079.2015.1086577