A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand
A stochastic multiproduct capacitated facility location problem involving a single supplier and multiple customers is investigated. Due to the stochastic demands, a reasonable amount of safety stock must be kept in the facilities to achieve suitable service levels, which results in increased invento...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/826363 |
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| author | Jin Qin Hui Xiang Yong Ye Linglin Ni |
| author_facet | Jin Qin Hui Xiang Yong Ye Linglin Ni |
| author_sort | Jin Qin |
| collection | DOAJ |
| description | A stochastic multiproduct capacitated facility location problem involving a single supplier and multiple customers is investigated. Due to the stochastic demands, a reasonable amount of safety stock must be kept in the facilities to achieve suitable service levels, which results in increased inventory cost. Based on the assumption of normal distributed for all the stochastic demands, a nonlinear mixed-integer programming model is proposed, whose objective is to minimize the total cost, including transportation cost, inventory cost, operation cost, and setup cost. A combined simulated annealing (CSA) algorithm is presented to solve the model, in which the outer layer subalgorithm optimizes the facility location decision and the inner layer subalgorithm optimizes the demand allocation based on the determined facility location decision. The results obtained with this approach shown that the CSA is a robust and practical approach for solving a multiple product problem, which generates the suboptimal facility location decision and inventory policies. Meanwhile, we also found that the transportation cost and the demand deviation have the strongest influence on the optimal decision compared to the others. |
| format | Article |
| id | doaj-art-b90b7fb7bc684f008600ee8ef72b3f0f |
| institution | OA Journals |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-b90b7fb7bc684f008600ee8ef72b3f0f2025-08-20T02:23:31ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/826363826363A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic DemandJin Qin0Hui Xiang1Yong Ye2Linglin Ni3School of Traffic and Transportation Engineering, Central South University, Changsha 410075, ChinaSchool of Traffic and Transportation Engineering, Central South University, Changsha 410075, ChinaSchool of Traffic and Transportation Engineering, Central South University, Changsha 410075, ChinaBusiness Administration College, Zhejiang University of Finance & Economics, Hangzhou 310018, ChinaA stochastic multiproduct capacitated facility location problem involving a single supplier and multiple customers is investigated. Due to the stochastic demands, a reasonable amount of safety stock must be kept in the facilities to achieve suitable service levels, which results in increased inventory cost. Based on the assumption of normal distributed for all the stochastic demands, a nonlinear mixed-integer programming model is proposed, whose objective is to minimize the total cost, including transportation cost, inventory cost, operation cost, and setup cost. A combined simulated annealing (CSA) algorithm is presented to solve the model, in which the outer layer subalgorithm optimizes the facility location decision and the inner layer subalgorithm optimizes the demand allocation based on the determined facility location decision. The results obtained with this approach shown that the CSA is a robust and practical approach for solving a multiple product problem, which generates the suboptimal facility location decision and inventory policies. Meanwhile, we also found that the transportation cost and the demand deviation have the strongest influence on the optimal decision compared to the others.http://dx.doi.org/10.1155/2015/826363 |
| spellingShingle | Jin Qin Hui Xiang Yong Ye Linglin Ni A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand The Scientific World Journal |
| title | A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand |
| title_full | A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand |
| title_fullStr | A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand |
| title_full_unstemmed | A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand |
| title_short | A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand |
| title_sort | simulated annealing methodology to multiproduct capacitated facility location with stochastic demand |
| url | http://dx.doi.org/10.1155/2015/826363 |
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