Particle Swarms Cooperative Optimization for Coalition Generation Problem
In this paper, a Particle Swarms Cooperative Optimization is proposed to solve Coalition Generation Problem in parallel manner with each Agent taking part in several different coalitions and each coalition turning its hand to several different tasks. With a novel two-dimensional binary encoding approach, the algorithm performs well on coalition parallel generation. An adaptive disturbance factor is adopted to force swarms getting out of local optimums quickly. Introduced an active-feedback based on island models, the algorithm has a good cooperative searching characteristic. The effectiveness of the proposed algorithm is proved by experiments.
KeywordsParticle Swarm Coalition Structure Island Model Discrete Particle Swarm Optimization Maximum Iteration Number
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