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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jin Peng Zhang Shu Chu |
| Copyright Year | 2010 |
| Description | Author affiliation: The School of Management, Hefei University of Technology, Key Laboratory Process Optimization and Intelligent, Decision-making, Ministry of Education, Hefei, Anhui Province, China (Jin Peng; Zhang Shu Chu) |
| Abstract | This study presents a new hybrid ant colony algorithm (HACO) to solve an in integer linear programming formulation of the Cutting Stock Problem(CSP). The CSP is an important class combinatorial problem. It is appropriate to minimize the raw material used by industries for fulfilling customer's demands. In such cases, classic models for solving the cutting stock problem are useless. HACO consists of GDCP procedure and modified ACO (MACO). GDCP procedure provides dominative cutting patterns as MACO solution components, in MACO the pheromone trail is put on cutting patterns instead of items. MACO preserves cutting patterns and frequencies information under ants building solution procedure. Results obtained from computational experiments for ten benchmarks demonstrate that the performance of MACO is compared to that obtained using existing mete-heuristic algorithm. |
| Starting Page | 32 |
| Ending Page | 35 |
| File Size | 238192 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424490875 |
| e-ISBN | 9781424490905 |
| DOI | 10.1109/FITME.2010.5654897 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-09 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ant Colony Algorithm Cutting Stock Problem Optimized production technology Bismuth Benchmark testing Integer linear programming dominative cutting pattern |
| Content Type | Text |
| Resource Type | Article |
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