教師資料查詢 | 類別: 會議論文 | 教師: 劉艾華 Liou, Ay-hwa Andy (瀏覽個人網頁)

標題:Improving Genetic Algorithms with Solution Space Partitioning and Evolution Refinements
學年96
學期1
發表日期2007/08/24
作品名稱Improving Genetic Algorithms with Solution Space Partitioning and Evolution Refinements
作品名稱(其他語言)
著者Liou, Ay-hwa Andy; Chi, Tzong-heng; Yu, I-jun
作品所屬單位淡江大學資訊管理學系
出版者
會議名稱Natural Computation, 2007. ICNC 2007. Third International Conference on
會議地點Haikou, China
摘要Irregular sum problem (ISP) is an issue resulted from mathematical problems and graph theories. It has the characteristic that when the problem size is getting bigger, the space of the solution is also become larger. Therefore, while searching for the feasible solution, the larger the question the harder the attempt to come up with an efficient search. We propose a new genetic algorithm, called the Incremental Improving Genetic Algorithm (IIGA), which is considered efficient and has the capability to incrementally improve itself from partial solutions. The initial solutions can be constructed by satisfying the constraints in stepwise fashion. The effectiveness of IIGA also comes from the allowing of suitable percentage of illegal solutions during the evolution for increasing the effectiveness of searching. The cut-point of the genetic coding for generating the descendants has carefully planned so that the algorithm can focus on the key factors for the contradiction and has the chances to fix it. After comparing the results of IIGA and usual genetic algorithm among different graphs, we found and shown that the performance of IIGA is truly better.
關鍵字Evolution Refinement;Genetic Algorithms;Graph Theory;Irregularity Sum;Problem Decomposition
語言英文
收錄於
會議性質國際
校內研討會地點
研討會時間20070824~20070827
通訊作者
國別中國
公開徵稿Y
出版型式
出處Natural Computation, 2007. ICNC 2007. Third International Conference on, v.4, pp.238-242
相關連結
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