Design of supply-chain logistics system considering service level
This research is concerned with an logistics system design which optimizes the performance of logistics system subject to required service levels both in the number of warehouse or distribution centers (W/D) and vehicle routing schedule. In this paper, the logistics system includes plants, W/D and c...
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Published in | Computers & industrial engineering Vol. 43; no. 1; pp. 283 - 297 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
New York
Elsevier Ltd
01.07.2002
Pergamon Press Inc |
Subjects | |
Online Access | Get full text |
ISSN | 0360-8352 1879-0550 |
DOI | 10.1016/S0360-8352(02)00075-X |
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Abstract | This research is concerned with an logistics system design which optimizes the performance of logistics system subject to required service levels both in the number of warehouse or distribution centers (W/D) and vehicle routing schedule. In this paper, the logistics system includes plants, W/D and customers. First, we formulated this problem using stochastic set-covering problem to determine the minimum number of W/D centers among a discrete set of location sites so that the probability of each customer to be covered is not less than a critical service level and solved this problem using 0–1 programming method. Then, we formulated a vehicle routing problem using an improved genetic algorithm and developed GUI-type programming based on three-step approaches such as: (1) clustering module which converges multi-supply center problem into single supply center problems, (2) improved vehicle routing, VRP module, and (3) GA-TSP module. For the users' conveniences, the sample results have been compared with those of existing methods. This research is strongly application oriented and the proposed model can be used to real world problems with some improvements. |
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AbstractList | This research is concerned with an logistics system design which optimizes the performance of logistics system subject to required service levels both in the number of warehouse or distribution centers (W/D) and vehicle routing schedule. In this paper, the logistics system includes plants, W/D and customers. First, this problem is formulated using stochastic set-covering problem to determine the minimum number of W/D centers among a discrete set of location sites so that the probability of each customer to be covered is not less than a critical service level and solved this problem using 0-1 programming method. Then, a vehicle routing problem was formulated using an improved genetic algorithm and developed GUI-type programming based on three-step approaches such as: 1. clustering module which converges multi-supply center problem into single supply center problems, 2. improved vehicle routing, VRP module, and 3. GA-TSP module. For the users' conveniences, the sample results have been compared with those of existing methods. This research is concerned with an logistics system design which optimizes the performance of logistics system subject to required service levels both in the number of warehouse or distribution centers (W/D) and vehicle routing schedule. In this paper, the logistics system includes plants, W/D and customers. First, we formulated this problem using stochastic set-covering problem to determine the minimum number of W/D centers among a discrete set of location sites so that the probability of each customer to be covered is not less than a critical service level and solved this problem using 0–1 programming method. Then, we formulated a vehicle routing problem using an improved genetic algorithm and developed GUI-type programming based on three-step approaches such as: (1) clustering module which converges multi-supply center problem into single supply center problems, (2) improved vehicle routing, VRP module, and (3) GA-TSP module. For the users' conveniences, the sample results have been compared with those of existing methods. This research is strongly application oriented and the proposed model can be used to real world problems with some improvements. |
Author | Hwang, Heung-Suk |
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Keywords | Logistics system design Stochastic set-covering problem Vehicle routing problem |
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References | Fisher, M. L. (1995). Gillet, Miller (BIB7) 1974; 22 Dor (BIB3) 1989; 23 Clarke, Wright (BIB2) 1964; 12 Grefenstette (BIB8) 1995 North-Holland, Anderson. Kuhn (BIB9) 1973; 4 Gendreau (BIB6) 1996; 88 Lin, Kernighan (BIB12) 1973 Sugal (1995), Genetic Algorithm Package, University of Sunderland, England. Kureichick, Melikhov (BIB10) 1996 Gendreau (10.1016/S0360-8352(02)00075-X_BIB6) 1996; 88 Grefenstette (10.1016/S0360-8352(02)00075-X_BIB8) 1995 Clarke (10.1016/S0360-8352(02)00075-X_BIB2) 1964; 12 Kuhn (10.1016/S0360-8352(02)00075-X_BIB9) 1973; 4 10.1016/S0360-8352(02)00075-X_BIB11 Dor (10.1016/S0360-8352(02)00075-X_BIB3) 1989; 23 Lin (10.1016/S0360-8352(02)00075-X_BIB12) 1973 Gillet (10.1016/S0360-8352(02)00075-X_BIB7) 1974; 22 Kureichick (10.1016/S0360-8352(02)00075-X_BIB10) 1996 10.1016/S0360-8352(02)00075-X_BIB4 |
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SubjectTerms | Logistics Logistics system design Mathematical models Optimization Routing Stochastic set-covering problem Studies Systems design Vehicle routing problem Vehicles |
Title | Design of supply-chain logistics system considering service level |
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