A New Particle Swarm Optimization Algorithm for Solve Problems in Continuous Scope

Particle Swarm Optimization (PSO) has been shown as an effective methodologyfor solving optimization problems over continuous scope. This algorithm has beenone of the most popular and used by researchers in real engineering design andeconomic problems. In this paper, the propose is proposing a new version of PSOalgorithm using improvement of the best solution in each iteration in addition togeneration of multipoint in the neighborhood and selection of the best solution ofall for next step. The goal of using this technique is increment of the explorationand exploitation, in other words, creation of a tradeoff between them. For testingthis algorithm, we used the important multiple and complex Benchmark function.The results were compared mathematically with the proposed function algorithmvia standard algorithm. It was shown that this technique could result in animproved exploration, local optima avoidance, exploitation and convergence.

کلیدواژه ها:

Global optimization ، Heuristics ، Particle Swarm Optimization ، Simulated Annealing