A Modified Particle Swarm Optimization Algorithm for Engineering Optimizations
نویسندگان
چکیده
Particle Swarm Optimization (PSO) is a population based optimal method and very simple in both theory and numerical implementation. Nowadays, PSO has been recognized as a paradigm for numerical optimizations; however, PSO is easily trapped into a local optimum when solving multidimensional and complex problems. In order to overcome this difficulty, this paper presents a modified PSO with a dynamic inertia weight and an adaptive mutation operator. To verify the proposed PSO, we test it numerically on a set of well known bench mark functions as well as on an engineering problem, as to which it has shown better performance and efficiency while compared to the basic PSO and Beta PSO.
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