Multiple Cooperating Swarms for Non-Linear Function Optimization
This paper investigates a new approach applied to particle swarm optimization. The paper addresses the idea of having multiple swarms searching for a solution while cooperating with each other by exchanging their best solutions. The experiments show that this approach behaves in a way that is dependent on the function being optimized. They also show that changing the synchronization period (number of generations) after which the swarms cooperate with each other has a great effect on the obtained solution quality.
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