A comparison study of harmony search and genetic algorithm for the max-cut problem

Abstract

The max-cut problem is one of well-known NP-complete problems and has applications in various fields such as the design process for VLSI (Very-Large-Scale Integration) chips and spin glass theory in statistical physics. In this paper, a harmony search algorithm for the max-cut problem is proposed. Compared to genetic algorithm, harmony search algorithm has advantages of generating a new vector after considering all of the existing vectors and requiring only a few number of parameters to be determined before the run of the algorithm. For 31 benchmark graphs of various types, the proposed harmony search algorithm is compared with a newly developed genetic algorithm and another genetic algorithm taken from the recent literature are presented. The proposed harmony search algorithm produced significantly better results than the two genetic algorithms.