Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem
碩士 === 立德管理學院 === 應用資訊研究所 === 94 === This thesis proposed a Tabu-Genetic Algorithm (Tabu-GA), which incorporates a traditional Genetic Algorithm (GA) and Tabu Search (TS), to solve the global optimization problems. The principle of the proposed algorithm is that we introduce the Tabu Search to perfo...
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ndltd-TW-094LU0055850132016-05-18T04:12:33Z http://ndltd.ncl.edu.tw/handle/96307008690348105811 Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem 基因演算法結合禁忌搜尋法之性能增益並應用於生產排程問題 Meng-Chun Chen 陳孟駿 碩士 立德管理學院 應用資訊研究所 94 This thesis proposed a Tabu-Genetic Algorithm (Tabu-GA), which incorporates a traditional Genetic Algorithm (GA) and Tabu Search (TS), to solve the global optimization problems. The principle of the proposed algorithm is that we introduce the Tabu Search to perform a fine tune in local search around neighbors on each individual within the population when an evolutionary generation of the GA is completed. Thus, the aim of the work is to find an acceptable optimal solution with less CPU time, and to enhance the poor efficiency in the local search for the traditional GA. This study used global optimization functions with high dimensions for the efficiency evaluation of the proposed algorithm. The numerical results using the present algorithm were compared with those results obtained using the traditional GA. Furthermore, the proposed algorithm is applied to the production scheduling problem and compared the algorithmic capability with other methods. Based on the solutions solved the aforementioned benchmarking tests and scheduling problem, the Tabu-Genetic Algorithm shown that it is a useful method for solving the global optimization problem with high capability and efficiency. Jenn-Long Liu 劉振隆 2006 學位論文 ; thesis 73 zh-TW |
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碩士 === 立德管理學院 === 應用資訊研究所 === 94 === This thesis proposed a Tabu-Genetic Algorithm (Tabu-GA), which incorporates a traditional Genetic Algorithm (GA) and Tabu Search (TS), to solve the global optimization problems. The principle of the proposed algorithm is that we introduce the Tabu Search to perform a fine tune in local search around neighbors on each individual within the population when an evolutionary generation of the GA is completed. Thus, the aim of the work is to find an acceptable optimal solution with less CPU time, and to enhance the poor efficiency in the local search for the traditional GA.
This study used global optimization functions with high dimensions for the efficiency evaluation of the proposed algorithm. The numerical results using the present algorithm were compared with those results obtained using the traditional GA. Furthermore, the proposed algorithm is applied to the production scheduling problem and compared the algorithmic capability with other methods. Based on the solutions solved the aforementioned benchmarking tests and scheduling problem, the Tabu-Genetic Algorithm shown that it is a useful method for solving the global optimization problem with high capability and efficiency.
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author2 |
Jenn-Long Liu |
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Jenn-Long Liu Meng-Chun Chen 陳孟駿 |
author |
Meng-Chun Chen 陳孟駿 |
spellingShingle |
Meng-Chun Chen 陳孟駿 Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem |
author_sort |
Meng-Chun Chen |
title |
Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem |
title_short |
Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem |
title_full |
Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem |
title_fullStr |
Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem |
title_full_unstemmed |
Performance Improvement of Combining Genetic Algorithm with Tabu Search and Apply to the Production Scheduling Problem |
title_sort |
performance improvement of combining genetic algorithm with tabu search and apply to the production scheduling problem |
publishDate |
2006 |
url |
http://ndltd.ncl.edu.tw/handle/96307008690348105811 |
work_keys_str_mv |
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