期刊論文
| 學年 | 94 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2006-01-01 |
| 作品名稱 | A Global Archive Sub-Population Genetic Algorithm with Adaptive Strategy in Multi-objective Parallel-Machine Scheduling Problem |
| 作品名稱（其他語言） | |
| 著者 | Pei-Chann Chang; Shih-Hsin Chen; Jih-Chang Hsieh |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Lecture Notes in Computer Science 4221, p.730-739 |
| 摘要 | This research extends the sub-population genetic algorithm and combines it with a global archive and an adaptive strategy to solve the multi-objective parallel scheduling problems. In this approach, the global archive is applied within each subpopulation and once a better Pareto solution is identified, other subpopulations are able to employ this Pareto solution to further guide the searching direction. In addition, the crossover and mutation rates are continuously adapted according to the performance of the current generation. As a result, the convergence and diversity of the evolutionary processes can be maintained in a very efficient manner. Intensive experimental results indicate that the sub-population genetic algorithm combing the global archive and the adaptive strategy outperforms NSGA II and SPEA II approaches. |
| 關鍵字 | |
| 語言 | en |
| ISSN | 0302-9743 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | DEU |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/121469 ) |