کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
380364 1437434 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A novel parallel multi-swarm algorithm based on comprehensive learning particle swarm optimization
ترجمه فارسی عنوان
یک الگوریتم چندگانه روان چندرسانه ای مبتنی بر بهینه سازی جامع یادگیری ذرات
کلمات کلیدی
بهینه سازی ذرات ذرات، الگوریتم موازی، بهینه ساز جامع یادگیری ذرات یادگیری، بهینه سازی جهانی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

This article presented a parallel metaheuristic algorithm based on the Particle Swarm Optimization (PSO) to solve global optimization problems. In recent years, many metaheuristic algorithms have been developed. The PSO is one of them is very effective to solve these problems. But PSO has some shortcomings such as premature convergence and getting stuck in local minima. To overcome these shortcomings, many variants of PSO have been proposed. The comprehensive learning particle swarm optimizer (CLPSO) is one of them. We proposed a better variation of CLPSO, called the parallel comprehensive learning particle swarm optimizer (PCLPSO) which has multiple swarms based on the master-slave paradigm and works cooperatively and concurrently. The PCLPSO algorithm was compared with nine PSO variants in the experiments. It showed a great performance over the other PSO variants in solving benchmark functions including their large scale versions. Besides, it solved extremely fast the large scale problems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 45, October 2015, Pages 33–45
نویسندگان
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