An Efficient Restart-Enhanced Genetic Algorithm for the Coalition Formation Problem

Abstract

In multi-agent system (MAS), the coalition formation (CF) is an important problem focusing on allocating agents to different tasks. In this paper, the single-task single-coalition (STSC) formation problem is considered. The mathematical model of the STSC problem is built with the objective of minimizing the total cost with the ability constraint. Besides, an efficient restart-enhanced genetic algorithm (REGA) is designed to solve the STSC problem. Furthermore, this paper constructs a comparison experiment, employing a random sampling method, an estimation of distribution algorithm and a genetic algorithm without restart strategy as competitors. The results of statistical analysis by the Wilcoxon’s rank-sum test demonstrate that the designed REGA performs better than its competitors in solving the STSC cases of different scales.