Effect of Inertia Weight w on PSO-SA Algorithm

Shigang Wang, Fangfang Zhou, Fengjuan Wang


Since particle swarm algorithm was proposed, because of its easy to understand and implement, the algorithm has been rapid development. However, the algorithm is easy to convergence, and the simulated annealing algorithm has strong local search ability, which can make the search process to avoid falling into local optimal solution. Because of the complementary of the advantages and disadvantages of the two algorithms, a new PSO-SA algorithm appears. This paper focuses on researching the effect of inertia weight of PSO-SA algorithm on the performance of the algorithm. PSO-SA algorithm is applied in solving the shortest path on curved surface, through an example to illustrate function of the inertia weight in algorithm.

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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