A DNA based evolutionary algorithm for the minimal set cover problem

Authors:
Wenbin Liu;Xiangou Zhu;Guandong Xu;Qiang Zhang;Lin Gao
Affiliations:
School of Computer Science and Engineering, Wenzhou Normal College, Wenzhou City, China;School of Computer Science and Engineering, Wenzhou Normal College, Wenzhou City, China;School of Computer Science and Engineering, Wenzhou Normal College, Wenzhou City, China;University Key Lab of Information Science & Engineering, Dalian University, Dalian, China;School of Computer, Xidian University, Xi' an city, China
Venue:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Year:
2005

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Abstract

With the birth of DNA computing, Paun et al. proposed an elegant algorithm to this problem based on the sticky model proposed by Roweis. However, the drawback of this algorithm is that the “exponential curse” is hard to overcome, and therefore its application to large instance is limited. In this s paper, we present a DNA based evolutionary algorithm to solve this problem, which takes advantage of both the massive parallelism and the evolution strategy by traditional EAs. The fitness of individuals is defined as the negative value of their length. Both the crossover and mutation can be implemented in a reshuffle process respectively. We also present a short discussion about population size, mutation probability, crossover probability, and genetic operations over multiple points. In the end, we also present some problems needed to be further considered in the future.