Abstract
Coalition structure generation in multi-agent systems has long been a challenging problem because of its NP-hardness in computational complexity. In this paper, we propose a stochastic optimization approach that employs a modified population based incremental learning algorithm and a customized genotype encoding scheme to find the optimal coalition structure for smart grids with renewable energy sources. Empirical results show that the proposed approach gives competitive performance compared with existing solutions such as genetic algorithm and dynamic programming.