On the running time analysis of the (1+1) evolutionary algorithm for the subset sum problem

Authors:
Yuren Zhou;Zhi Guo;Jun He
Affiliations:
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;School of Computer Science, University of Birmingham, Birmingham, UK
Venue:
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Year:
2007

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Abstract

Theoretic researches of evolutionary algorithms have received much attention in the past few years. This paper presents the running time analysis of evolutionary algorithm for the subset sum problems. The analysis is carried out on (1+1) EA for different subset sum problems. It uses the binary representation to encode the solutions, the method "superiority of feasible point" that separate objectives and constraints to handle the constraints, and the absorbing Markov chain model to analyze the expected runtime. It is shown that the mean first hitting time of (1+1) EA for solving subset sum problems may be polynomial, exponential, or infinite.