The development of a Sub-Population Genetic Algorithm II (SPGAII) for the Multi-objective Combinatorial Problems
學年 97
學期 1
出版（發表）日期 2009-01-01
作品名稱 The development of a Sub-Population Genetic Algorithm II (SPGAII) for the Multi-objective Combinatorial Problems
作品名稱（其他語言）
著者 Chang, P.C.; S. H. Chen
單位
出版者
著錄名稱、卷期、頁數 Applied Soft Computing Journal 9(1), p.173-181
摘要 Previous research has shown that sub-population genetic algorithm is effective in solving the multi-objective combinatorial problems. Based on these pioneering efforts, this paper extends the SPGA algorithm with a global Pareto archive technique and a two-stage approach to solve the multi-objective problems. In the first stage, the areas next to the two single objectives are searched and solutions explored around these two extreme areas are reserved in the global archive for later evolutions. Then, in the second stage, larger searching areas except the middle area are further extended to explore the solution space in finding the near-optimal frontiers. Through extensive experimental results, SPGA II does outperform SPGA, NSGA II, and SPEA 2 in the parallel scheduling problems and knapsack problems; it shows that the approach improves the sub-population genetic algorithm significantly. It may be of interests for researchers in solving multi-objective combinatorial problems.
關鍵字 Genetic algorithm;Parallel scheduling problems;Multidimensional knapsack problem;Multi-objective optimization
語言 en
ISSN 1872-9681
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 NLD
公開徵稿
出版型式 ,電子版,紙本
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機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/121436 )