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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Vydáno v:International journal of general systems Ročník 45; číslo 3; s. 286 - 310
Hlavní autoři: Du, Jiaoman, Yu, Lean, Li, Xiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 02.04.2016
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ISSN:0308-1079, 1563-5104
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Abstract 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.
AbstractList 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.
Author Du, Jiaoman
Li, Xiang
Yu, Lean
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  surname: Yu
  fullname: Yu, Lean
  organization: School of Economics and Management, Beijing University of Chemical Technology
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  givenname: Xiang
  surname: Li
  fullname: Li, Xiang
  email: lixiang@mail.buct.edu.cn
  organization: School of Economics and Management, Beijing University of Chemical Technology
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Snippet Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy...
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SubjectTerms 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
Title Fuzzy multi-objective chance-constrained programming model for hazardous materials transportation
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