Coalition Formation Mechanism in Multi-Agent System Based on Genetic Algorithm

An an important coordination and cooperation mechanism in multi-agent system, agent coalition exhibits some excellent characteristics and attracts our attention increasingly. An efficient algorithm is needed for this topic since the number of the possible coalitions is exponential. Genetic Algorithm (GA) has been widely reckoned as a useful tool for obtaining high quality or even optimal solutions for a broad range of the combinatorial optimization problems due to its intelligent advantages of self-organization, self-adaptation and inherent parallelism. This paper proposes a GA-based algorithm with an objective to simultaneously meet the goals of high performance, scalability, and fast running time. A novel two-dimensional binary chromosome encoding approach and corresponding crossover and mutation operators are presented in this paper. Two valid parental chromosomes are certain to produce a valid offspring under the operation of the crossover operation. This improves the efficiency and reduces the running time greatly. The proposed algorithm is evaluated through a robust comparison with a heuristics. The experimental results have demonstrated that our algorithm is robust, self-adaptive and very efficient.