بهبود الگوریتم های بهینه سازی اجتماع ذرات و تکامل تفاضلی با استفاده از نظریه چانه زنی نش
الموضوعات :
مرضیه دادور
1
,
حمید رضا نویدی
2
,
حمید حاج سید جوادی
3
,
میترا میرزارضایی
4
1 - گروه مهندسی کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
2 - گروه ریاضیات و علوم کامپیوتر، دانشگاه شاهد، تهران، ایران
3 - گروه ریاضیات و علوم کامپیوتر، دانشگاه شاهد، تهران، ایران
4 - گروه مهندسی کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
الکلمات المفتاحية: بهینه سازی ازدحام ذرات (PSO), تکامل تفاضلی (DE), تئوری بازی همکارانه , نظریه چانه زنی نش .,
ملخص المقالة :
این مقاله، رویکرد جدیدی را به منظور حل مسائل بهینهسازی ارائه میکند، که دو الگوریتم شناخته شده‌ی بهینهسازی ازدحام ذرات (Particle Swarm Optimization) و تکامل تفاضلی (Differential Evolution) با هم همکاری می‌نماید. در رویکرد پیشنهادی برای حفظ تعادل بین توانایی اکتشاف و استخراج با جلوگیری از سکون جمعیت، اجتناب از بهینه محلی و بهبود در الگوریتمهای PSO و DE از مدل ائتلافی یا همکاری در تئوری بازی‌ها استفاده می‌شود. در واقع الگوریتمهای PSO و DE به عنوان دو بازیکن در فضای جستجو هستند، که با استفاده نظریه چانه زنینش (Nash bargaining theory) در هر مرحله با هم بازی همکارانه (Cooperative game) انجام داده تا بهترین راهحل را در فضای جستجو بدست آورند. مطابق با ساختارCEC2005، بیست و پنج تابع معیار (Benchmark functions) برای ارزیابی کارایی الگوریتم پیشنهادی مورد استفاده قرار می‌گیرند. روش پیشنهادی با دو الگوریتم کلاسیک PSO وDE و الگوریتمهای ترکیبی که اخیرا پیشنهاد شده است مقایسه می‌شود. نتایج نشان می‌دهد، رویکرد ارائه شده در مقایسه با الگوریتمهای کلاسیک و سایر مدل های ترکیبی عملکرد بهتری دارد.
The game environment creates a competitive environment between algorithms and greatly increases the searching ability of the algorithms.
The profit earned from Nash bargaining is the best solution for both algorithms due to their Pareto optimality property.
The exchange of profits earned from the game between the algorithms leads to exploring new areas in the search environment, increasing diversity, and avoiding the local optimum.
The condition of the Nash bargaining theorem helps to maintain a balance between the exploration and exploitation capabilities in the proposed method.
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