Hybrid genetic algorithm for minimum dominating set problem

Abstract

The minimum dominating set (MDS) problem is one of the central problems of algorithmic graph theory and has numerous applications especially in graph mining. In this paper, we propose a new hybrid method based on genetic algorithm (GA) to solve the MDS problem, called shortly HGA-MDS. The proposed method invokes a new fitness function to effectively measure the solution qualities. The search process in HGA-MDS uses local search and intensification schemes beside the GA search methodology in order to achieve faster performance. Finally, the performance of the HGA-MDS is compared with the standard GA. The new invoked design elements in HGA-MDS show its promising performance compared with standard GA. © 2010 Springer-Verlag Berlin Heidelberg.