Unit Bit Importance Evolutionary Algorithm

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• 作者：Yi Hong ; Qingsheng Ren and Jin Zeng
• 关键词：Genetic algorithms ; Bit importance ; Convergent order of bit ; Weighted probability
• 刊名：Soft Computing - A Fusion of Foundations, Methodologies and Applications
• 出版年：2007
• 出版时间：January, 2007
• 年：2007
• 卷：11
• 期：2
• 页码：115-122
• 全文大小：207 KB
• 刊物类别：Engineering
• 刊物主题：Numerical and Computational Methods in Engineering
  Theory of Computation
  Computing Methodologies
  Mathematical Logic and Foundations
  Control Engineering
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1433-7479

文摘

In Darwinian-type binary-coded genetic algo- rithms, there exist bit importance and convergent order of bit. Inspired from this phenomenon, we propose an evolutionary algorithm called Unit Bit Importance Evolutionary Algorithm (UBIEA). Compared with Darwinian-type genetic algorithms, UBIEA completely abandons commonly used genetic operators such as mutation and crossover. Its main idea is that: detecting bit importance, speeding up the convergence of important bits and maintaining the diversity of unimportant bits. Although our theoretic analyses are based on the assumption that all bits are independent and have different salience, UBIEA perhaps is usable in a larger framework which can be verified by numerical experiments.