دانلود مقاله A New Collaborative Paradigm for Coدرevolutionary Particle Swarm Optimization: Equippe
دانلود مقاله A New Collaborative Paradigm for Coدرevolutionary Particle Swarm Optimization: Equipped with Skepticism Parameter, Group Energizer and Pseudo Random Initialization در فایل ورد (word) دارای 6 صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است
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بخشی از متن دانلود مقاله A New Collaborative Paradigm for Coدرevolutionary Particle Swarm Optimization: Equipped with Skepticism Parameter, Group Energizer and Pseudo Random Initialization در فایل ورد (word) :
سال انتشار: 1392
محل انتشار: بیست و یکمین کنفرانس مهندسی برق ایران
تعداد صفحات: 6
چکیده:
Considerable number of studies confirm a remarkable performance for evolutionary algorithms (EAs); however, this performance deteriorates as EAs face large scale non-separableproblems. This paper proposes a new collaborative approach based on a co-evolutionary framework for solving large scale nonseparableproblems. Here, collaboration means using more interactive and intelligent particles in a search space for faster butnot premature convergence. Proposed ideas for Collaborative CoevolutionaryParticle Swarm Optimization (CLCPSO) are summarized in the following three items. First is adding Skepticism parameter” to redistribute particles with Cauchy and Gaussian distributions, when the algorithm for two sequential runsshows same result. Second is adaptively tuning group diversity to overcome the problem of trapping in local optima, by adding anew particle called Group energizer to call for random topology when the best fit particle has reached a certain age. Third is using a pseudo random number instead of random number for population initialization. Results show that these techniques improve the convergence issue. Application to several CEC2010benchmarks and comparison against several state-of-the-art approaches such as cooperative co-volutionary particle swarm optimization (CCPSO) confirm the merits of the approach.
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