Abstract
In this paper, a hybrid particle swarm optimization called discrete local particle swarm optimization is proposed. The new method combines the global search ability of the particle swarm optimization and the precise search ability of the local search algorithm. A discrete particle swarm optimization is used in this method to rapidly find an approximate discrete solution which is near the final continuous solution. Then a local search algorithm is used based on this discrete solution to get a more accurate solution, which makes the discrete solution continuous. The improved algorithm is applied to six benchmark functions and the results show that this algorithm is usually more rapid and precise than the classical particle swarm optimization.
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