History Information Based Optimization of Additively Decomposed Function with Constraints

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• 作者：Qingsheng Ren ; Jin Zeng ; Feihu Qi
• 刊名：Lecture Notes in Computer Science
• 出版年：2004
• 出版时间：2004
• 年：2004
• 卷：3314
• 期：1
• 全文大小：109 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In this paper, we propose a modified estimation of distribution algorithm HCFA (History information based Constraint Factorization Algorithm) to solve the optimization problem of additivelydecomposed function with constraints. It is based on factorized distribution instead of penalty function and any transformation to a linear model or others. The history information is used and good results can be achieved with small population size. The feasibility of the new algorithm is also given.