Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior
Location-allocation of facilities in service systems is an essential factor of their performance. One of the considerable situations which less addressed in the relevant literature is to balance service among customers in addition to minimize location-allocation costs. This is an important issue, es...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Iran University of Science & Technology
2013-09-01
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| Series: | International Journal of Industrial Engineering and Production Research |
| Subjects: | |
| Online Access: | http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-455-1&slc_lang=en&sid=1 |
| _version_ | 1819266831959982080 |
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| author | Jafar Bagherinejad Maryam Omidbakhsh |
| author_facet | Jafar Bagherinejad Maryam Omidbakhsh |
| author_sort | Jafar Bagherinejad |
| collection | DOAJ |
| description | Location-allocation of facilities in service systems is an essential factor of their performance. One of the considerable situations which less addressed in the relevant literature is to balance service among customers in addition to minimize location-allocation costs. This is an important issue, especially in the public sector. Reviewing the recent researches in this field shows that most of them allocated demand customer to the closest facility. While, using probability rules to predict customer behavior when they select the desired facility is more appropriate. In this research, equitable facility location problem based on the gravity rule was investigated. The objective function has been defined as a combination of balancing and cost minimization, keeping in mind some system constraints. To estimate demand volume among facilities, utility function(attraction function) added to model as one constraint. The research problem is modeled as one mixed integer linear programming. Due to the model complexity, two heuristic and genetic algorithms have been developed and compared by exact solutions of small dimension problems. The results of numerical examples show the heuristic approach effectiveness with good-quality solutions in reasonable run time. |
| first_indexed | 2024-12-23T21:07:32Z |
| format | Article |
| id | doaj.art-1beaa3342c7b476d9bf8a41c1a93b0b1 |
| institution | Directory Open Access Journal |
| issn | 2008-4889 2345-363X |
| language | English |
| last_indexed | 2024-12-23T21:07:32Z |
| publishDate | 2013-09-01 |
| publisher | Iran University of Science & Technology |
| record_format | Article |
| series | International Journal of Industrial Engineering and Production Research |
| spelling | doaj.art-1beaa3342c7b476d9bf8a41c1a93b0b12022-12-21T17:31:10ZengIran University of Science & TechnologyInternational Journal of Industrial Engineering and Production Research2008-48892345-363X2013-09-01243217227Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer BehaviorJafar Bagherinejad0Maryam Omidbakhsh1 University of Alzahra Alzahra Univ Location-allocation of facilities in service systems is an essential factor of their performance. One of the considerable situations which less addressed in the relevant literature is to balance service among customers in addition to minimize location-allocation costs. This is an important issue, especially in the public sector. Reviewing the recent researches in this field shows that most of them allocated demand customer to the closest facility. While, using probability rules to predict customer behavior when they select the desired facility is more appropriate. In this research, equitable facility location problem based on the gravity rule was investigated. The objective function has been defined as a combination of balancing and cost minimization, keeping in mind some system constraints. To estimate demand volume among facilities, utility function(attraction function) added to model as one constraint. The research problem is modeled as one mixed integer linear programming. Due to the model complexity, two heuristic and genetic algorithms have been developed and compared by exact solutions of small dimension problems. The results of numerical examples show the heuristic approach effectiveness with good-quality solutions in reasonable run time.http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-455-1&slc_lang=en&sid=1Facility location Equitable load Gravity model Heuristic algorithm Genetic algorithm Integer programming |
| spellingShingle | Jafar Bagherinejad Maryam Omidbakhsh Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior International Journal of Industrial Engineering and Production Research Facility location Equitable load Gravity model Heuristic algorithm Genetic algorithm Integer programming |
| title | Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior |
| title_full | Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior |
| title_fullStr | Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior |
| title_full_unstemmed | Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior |
| title_short | Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior |
| title_sort | approximation methods for solving the equitable location problem with probabilistic customer behavior |
| topic | Facility location Equitable load Gravity model Heuristic algorithm Genetic algorithm Integer programming |
| url | http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-455-1&slc_lang=en&sid=1 |
| work_keys_str_mv | AT jafarbagherinejad approximationmethodsforsolvingtheequitablelocationproblemwithprobabilisticcustomerbehavior AT maryamomidbakhsh approximationmethodsforsolvingtheequitablelocationproblemwithprobabilisticcustomerbehavior |