A Stone Resource Assignment Model under the Fuzzy Environment

This paper proposes a bilevel multiobjective optimization model with fuzzy coefficients to tackle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. On the upper level, the local government wants to assign a reasonable exploitation amount to each stone pla...

Full description

Bibliographic Details
Main Authors: Liming Yao, Jiuping Xu, Feng Guo
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2012/265837
id doaj-191afe368ecf46ec9fc3524a4dda7e18
record_format Article
spelling doaj-191afe368ecf46ec9fc3524a4dda7e182020-11-24T21:54:34ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/265837265837A Stone Resource Assignment Model under the Fuzzy EnvironmentLiming Yao0Jiuping Xu1Feng Guo2Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, ChinaUncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, ChinaUncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, ChinaThis paper proposes a bilevel multiobjective optimization model with fuzzy coefficients to tackle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. On the upper level, the local government wants to assign a reasonable exploitation amount to each stone plant so as to minimize total emissions and maximize employment and economic profit. On the lower level, stone plants must reasonably assign stone resources to produce different stone products under the exploitation constraint. To deal with inherent uncertainties, the object functions and constraints are defuzzified using a possibility measure. A fuzzy simulation-based improved simulated annealing algorithm (FS-ISA) is designed to search for the Pareto optimal solutions. Finally, a case study is presented to demonstrate the practicality and efficiency of the model. Results and a comparison analysis are presented to highlight the performance of the optimization method, which proves to be very efficient compared with other algorithms.http://dx.doi.org/10.1155/2012/265837
collection DOAJ
language English
format Article
sources DOAJ
author Liming Yao
Jiuping Xu
Feng Guo
spellingShingle Liming Yao
Jiuping Xu
Feng Guo
A Stone Resource Assignment Model under the Fuzzy Environment
Mathematical Problems in Engineering
author_facet Liming Yao
Jiuping Xu
Feng Guo
author_sort Liming Yao
title A Stone Resource Assignment Model under the Fuzzy Environment
title_short A Stone Resource Assignment Model under the Fuzzy Environment
title_full A Stone Resource Assignment Model under the Fuzzy Environment
title_fullStr A Stone Resource Assignment Model under the Fuzzy Environment
title_full_unstemmed A Stone Resource Assignment Model under the Fuzzy Environment
title_sort stone resource assignment model under the fuzzy environment
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2012-01-01
description This paper proposes a bilevel multiobjective optimization model with fuzzy coefficients to tackle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. On the upper level, the local government wants to assign a reasonable exploitation amount to each stone plant so as to minimize total emissions and maximize employment and economic profit. On the lower level, stone plants must reasonably assign stone resources to produce different stone products under the exploitation constraint. To deal with inherent uncertainties, the object functions and constraints are defuzzified using a possibility measure. A fuzzy simulation-based improved simulated annealing algorithm (FS-ISA) is designed to search for the Pareto optimal solutions. Finally, a case study is presented to demonstrate the practicality and efficiency of the model. Results and a comparison analysis are presented to highlight the performance of the optimization method, which proves to be very efficient compared with other algorithms.
url http://dx.doi.org/10.1155/2012/265837
work_keys_str_mv AT limingyao astoneresourceassignmentmodelunderthefuzzyenvironment
AT jiupingxu astoneresourceassignmentmodelunderthefuzzyenvironment
AT fengguo astoneresourceassignmentmodelunderthefuzzyenvironment
AT limingyao stoneresourceassignmentmodelunderthefuzzyenvironment
AT jiupingxu stoneresourceassignmentmodelunderthefuzzyenvironment
AT fengguo stoneresourceassignmentmodelunderthefuzzyenvironment
_version_ 1725867145176285184