The cooperation of agents in smart grids to form coalitions could bring benefit both for the agent itself and the distribution power system. To tackle the problem as a game of partition form functions poses significant computing challenges due to the huge search space for the optimization problem. In this seminar, we present a stochastic optimization approach using the Population-Based Incremental Learning (PBIL) algorithm with Top-k Merit Weighting and a customized strategy for choosing the initial probability to solve the problem. Empirical results show that the proposed algorithm gives competitive performance compared with a few stochastic optimization algorithms.
Last modified: Wednesday, 16-Aug-2017 09:01:53 NZST
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