History information based optimization of additively decomposed function with constraints

Authors:
Qingsheng Ren;Jin Zeng;Feihu Qi
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, P.R. China;Department of Mathematics, Shanghai Jiaotong University, Shanghai, P.R. China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, P.R. China
Venue:
CIS'04 Proceedings of the First international conference on Computational and Information Science
Year:
2004

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Abstract

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.