کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
847228 909222 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-objective quantum-behaved particle swarm optimization algorithm with double-potential well and share-learning
ترجمه فارسی عنوان
الگوریتم بهینه سازی ذرات چند جانبه رفتار شده با کوانتومی با دو پتانسیل خوب و یادگیری سهم
کلمات کلیدی
چاه کوانتومی دو پتانسیل، بهینه سازی ذرات ذرات، بهینه سازی چند هدفه، به اشتراک گذاری یادگیری
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی (عمومی)
چکیده انگلیسی

For improving the convergence accuracy and diversity of multi-objective optimization algorithm a multi-objective quantum-behaved particle swarm optimization algorithm with double-potential well and share-learning is proposed, which overcomes the deficiency of particles readily gathering in identical solutions. The two local attractors, inside and outside, are introduced to construct the particle locations updating model, using the quantum tunneling and transition effects in double-potential well model. In this way, the particle moves to the solution sparseness region in later evolution stage, so as to avoid gathering in the single local attractor and escape from local optimum. Therefore the optimization accuracy of the algorithm is improved. The share-learning strategy is adopted to extend the search range of particles and increase the diversity of solutions. The problem of easily converging to boundary solutions in quantum-behaved particle swarm optimization algorithm could be avoided. Simulation results show that the proposed algorithm makes excellent performance in optimization accuracy, convergence, diversity, and distribution, compared with three existing algorithms. Moreover, the proposed algorithm can hold on better convergence and distribution performance when handling high-dimensional multi-objective problems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Optik - International Journal for Light and Electron Optics - Volume 127, Issue 12, June 2016, Pages 4921–4927
نویسندگان
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