کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10139493 | 1645964 | 2018 | 32 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A dynamic multiple populations particle swarm optimization algorithm based on decomposition and prediction
ترجمه فارسی عنوان
یک الگوریتم بهینه سازی ذرات چندگانه جمعیت پویا با استفاده از تجزیه و پیش بینی
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کلمات کلیدی
بهینه سازی چند هدفه پویا، جمعیت چندگانه، تجزیه فضای هدف، مکانیزم پیش بینی جمعیت بهینه سازی ذرات ذرات،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Dynamic multi-objective optimization problems (DMOPs) involve multiple optimization objectives which are in conflict with one another and change over time or environment. A novel dynamic multiple population particle swarm optimization algorithm based on decomposition and prediction (denoted as DP-DMPPSO) is proposed to solve DMOPs. Each objective is optimized by one population and each population shares their information with other populations. The populations evolve independently using a modified particle swarm optimization (PSO). An external archive is adopted to store the non-dominated solutions selected from all populations in the evolutionary process and the archive will be output as the final solution. A mechanism for updating the archive based on the objective space decomposition (DOS) is proposed. In addition, a population prediction mechanism is employed to accelerate the convergence to the true Pareto front. DP-DMPPSO is tested on a set of benchmark problems and compared with several state-of-the-art algorithms. The results show DP-DMPPSO is highly competitive for solving dynamic multi-objective optimization problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 73, December 2018, Pages 434-459
Journal: Applied Soft Computing - Volume 73, December 2018, Pages 434-459
نویسندگان
Ruochen Liu, Jianxia Li, Jing Fan, Licheng Jiao,