Vendor managed inventory control system for deteriorating items using metaheuristic algorithms
Inventory control of deteriorating items constitutes a large part of the world’s economy and covers various goods including any commodity, which loses its worth over time because of deterioration and/or obsolescence. Vendor managed inventory (VMI), which is a win-win strategy for both suppliers and...
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| Vydané v: | Decision Science Letters Ročník 7; číslo 1; s. 25 - 38 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Growing Science
2018
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| ISSN: | 1929-5804, 1929-5812 |
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| Abstract | Inventory control of deteriorating items constitutes a large part of the world’s economy and covers various goods including any commodity, which loses its worth over time because of deterioration and/or obsolescence. Vendor managed inventory (VMI), which is a win-win strategy for both suppliers and buyers gains better results than traditional supply chain. In this research, we study an economic order quantity (EOQ) with shortage in form of partial backorder under VMI policy. The model is concerned with multi-item subject to multi-constraint including storage space, time period and budget constraints. Two metaheuristic algorithms, namely Simulated Annealing and Tabu Search, are used to find a near optimal solution for the proposed fuzzy nonlinear integer-programming problem with the objective of minimizing the total cost of the supply chain. Furthermore, the sensitivity analysis of the metaheuristic parameters is performed and five numerical examples containing different numbers of items are conducted in order to evaluate the performance of the algorithms. |
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| AbstractList | Inventory control of deteriorating items constitutes a large part of the world’s economy and covers various goods including any commodity, which loses its worth over time because of deterioration and/or obsolescence. Vendor managed inventory (VMI), which is a win-win strategy for both suppliers and buyers gains better results than traditional supply chain. In this research, we study an economic order quantity (EOQ) with shortage in form of partial backorder under VMI policy. The model is concerned with multi-item subject to multi-constraint including storage space, time period and budget constraints. Two metaheuristic algorithms, namely Simulated Annealing and Tabu Search, are used to find a near optimal solution for the proposed fuzzy nonlinear integer-programming problem with the objective of minimizing the total cost of the supply chain. Furthermore, the sensitivity analysis of the metaheuristic parameters is performed and five numerical examples containing different numbers of items are conducted in order to evaluate the performance of the algorithms. |
| Author | Rabbani, Masoud Rezaei, Hamidreza Lashgari, Mohsen Farrokhi-Asl, Hamed |
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| CitedBy_id | crossref_primary_10_1007_s42524_025_4110_6 crossref_primary_10_1007_s10115_025_02481_8 crossref_primary_10_1016_j_eswa_2023_119608 crossref_primary_10_1007_s42452_024_06423_x crossref_primary_10_1038_s41598_025_09875_2 crossref_primary_10_1007_s13198_025_02777_6 crossref_primary_10_1007_s11301_023_00374_0 crossref_primary_10_1007_s11740_025_01351_0 crossref_primary_10_1016_j_asoc_2024_111905 crossref_primary_10_1016_j_cie_2019_106156 |
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| SubjectTerms | Deteriorating items Economic order quantity Fuzzy Metaheuristic algorithm Vendor managed inventory |
| Title | Vendor managed inventory control system for deteriorating items using metaheuristic algorithms |
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