Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty

This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuz...

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Main Author: Xuejie Bai
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2016/2823835
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spelling doaj-7625924600c846cbab736c3a6e7b04802020-11-24T22:29:36ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/28238352823835Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated UncertaintyXuejie Bai0College of Science, Hebei Agricultural University, Baoding, Hebei 071001, ChinaThis paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method.http://dx.doi.org/10.1155/2016/2823835
collection DOAJ
language English
format Article
sources DOAJ
author Xuejie Bai
spellingShingle Xuejie Bai
Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty
Mathematical Problems in Engineering
author_facet Xuejie Bai
author_sort Xuejie Bai
title Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty
title_short Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty
title_full Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty
title_fullStr Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty
title_full_unstemmed Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty
title_sort two-stage multiobjective optimization for emergency supplies allocation problem under integrated uncertainty
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2016-01-01
description This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method.
url http://dx.doi.org/10.1155/2016/2823835
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