Fuzzy random programming models for location-allocation problem with applications

Shuya Zhong; Yizeng Chen; Jian Zhou

doi:10.1016/j.cie.2014.11.013

Fuzzy random programming models for location-allocation problem with applications

Shuya Zhong, Yizeng Chen, Jian Zhou

Shanghai University

Research output: Contribution to journal › Article › peer-review

13 Citations (SciVal)

Abstract

Three types of fuzzy random programming models based on the mean chance for the capacitated location-allocation problem with fuzzy random demands are proposed according to different criteria, including the expected cost minimization model, the α-cost minimization model, and the chance maximization model. In order to solve the proposed models, some hybrid intelligent algorithms are designed by integrating the network simplex algorithm, fuzzy random simulation, and genetic algorithm. Finally, some numerical examples about a container freight station problem are given to illustrate the effectiveness of the devised algorithms.

Original language	English
Pages (from-to)	194-202
Number of pages	9
Journal	Computers and Industrial Engineering
Volume	89
DOIs	https://doi.org/10.1016/j.cie.2014.11.013
Publication status	E-pub ahead of print - 2 Dec 2014

Bibliographical note

Funding Information:
This work was supported by grants from the National Social Science Foundation of China (No. 13CGL057 ), the National Natural Science Foundation of China (No. 71272177 ), and the Ministry of Education Funded Project for Humanities and Social Sciences Research (No. 12JDXF005 ).

Funding

This work was supported by grants from the National Social Science Foundation of China (No. 13CGL057 ), the National Natural Science Foundation of China (No. 71272177 ), and the Ministry of Education Funded Project for Humanities and Social Sciences Research (No. 12JDXF005 ).

Keywords

Fuzzy random programming
Genetic algorithm
Location-allocation problem
Simulation

ASJC Scopus subject areas

General Computer Science
General Engineering

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10.1016/j.cie.2014.11.013

Cite this

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abstract = "Three types of fuzzy random programming models based on the mean chance for the capacitated location-allocation problem with fuzzy random demands are proposed according to different criteria, including the expected cost minimization model, the α-cost minimization model, and the chance maximization model. In order to solve the proposed models, some hybrid intelligent algorithms are designed by integrating the network simplex algorithm, fuzzy random simulation, and genetic algorithm. Finally, some numerical examples about a container freight station problem are given to illustrate the effectiveness of the devised algorithms.",

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AU - Chen, Yizeng

AU - Zhou, Jian

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AB - Three types of fuzzy random programming models based on the mean chance for the capacitated location-allocation problem with fuzzy random demands are proposed according to different criteria, including the expected cost minimization model, the α-cost minimization model, and the chance maximization model. In order to solve the proposed models, some hybrid intelligent algorithms are designed by integrating the network simplex algorithm, fuzzy random simulation, and genetic algorithm. Finally, some numerical examples about a container freight station problem are given to illustrate the effectiveness of the devised algorithms.

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KW - Genetic algorithm

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Fuzzy random programming models for location-allocation problem with applications

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

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