建構整合型基因演算法最佳化主動運補路線建構整合型基因演算法最佳化主動運補路線建構整合型基因演算法最佳化主動運補路線
碩士 === 國防大學中正理工學院 === 兵器系統工程研究所 === 95 === The complexity of resolving vehicle routing problem is a NP-Hard (Non-deterministic Polynomial-time Hard) problem. Accordingly, conventional mathematical programming cannot efficiently applied in resolving VRP as numerous demand points are involved. Many s...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/53079056025522809288 |
| Summary: | 碩士 === 國防大學中正理工學院 === 兵器系統工程研究所 === 95 === The complexity of resolving vehicle routing problem is a NP-Hard (Non-deterministic Polynomial-time Hard) problem. Accordingly, conventional mathematical programming cannot efficiently applied in resolving VRP as numerous demand points are involved. Many studies utilized the meta-heuristic algorithm to determine a solution approaching the optimal solution. The genetic algorithm (GA) was verified an effective meta-heuristic algorithm. This study developed a hybrid GA model, combining K-mean technology and pure GA to further improve the effectiveness of GA in resolving VRP. A case involving optimization of local active distribution from militarily troops demonstrates the effectiveness of the proposed hybrid GA model.
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