توسعه الگوریتم تکامل شوراهای شهر برای حل مسائل بهینهسازی چندهدفه | ||
| محاسبات نرم | ||
| دوره 13، شماره 2 - شماره پیاپی 26، اسفند 1403، صفحه 56-77 اصل مقاله (619.47 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22052/scj.2024.253070.1154 | ||
| نویسندگان | ||
| مهدیه غفار علیشاهی؛ عین اله پیرا* ؛ علیرضا روحی | ||
| دانشکده فناوری اطلاعات و مهندسی کامپیوتر، دانشگاه شهید مدنی آذربایجان، تبریز، ایران. | ||
| چکیده | ||
| پیشرفت فناوری و ظهور مسائل بهینهسازی چندهدفه در شاخههای علوم مختلف باعث تحقیق و ارائه الگوریتمهای فراابتکاری جدید برای حل چنین مسائلی شدهاند. اگرچه این الگوریتمها تا حدودی توانستهاند تقریب به نسبت خوبی از جبهه بهینه پرِتو را پیدا کنند ولی هنوز بهینهسازی بهطور کامل انجام نشده است. در این مقاله، برای افزایش میزان بهینگی جبهه پرِتو تولید شده، نسخه چندهدفهای از الگوریتم تکامل شوراهای شهر (CCE) با نام الگوریتم تکامل شوراهای شهر چندهدفه (MOCCE) ارائه میشود. در الگوریتم ارائه شده، یک آرشیو با اندازه ثابت برای ذخیره و بازیابی راهحلهای بهینه پرِتو در نظر گرفته میشود. از این آرشیو برای تعریف ساختار هرمگونه شوراهای شهرها و شبیهسازی تکامل آن در فضاهای جستجوی چندهدفه استفاده میشود. کارایی الگوریتم MOCCE روی 18 تابع آزمون چندهدفه شناخته شده موسوم به UF و IMOP مورد ارزیابی قرار گرفته و با نتایج الگوریتمهای بهینهسازی شیر مورچه چندهدفه (MOALO)، کپک مخاطی چندهدفه (MOSMA) و مرغ مگسخوار مصنوعی چندهدفه (MOAHA) مقایسه شدهاند. مطابق با نتایج آزمون میانگین رتبه فریدمن، در همه توابع آزمون UF، الگوریتم MOCCE اولین رتبه را در بین الگوریتمهای مقایسه شده از لحاظ معیارهای فاصله نسلی (GD)، فاصله نسلی معکوس (IGD) و بیشینه گستردگی (MS) کسب میکند. همچنین، این الگوریتم اولین رتبه را در همه توابع آزمون IMOP از لحاظ معیار GD و دومین رتبه را از لحاظ معیارهای IGD و MS به خود اختصاص میدهد. | ||
| کلیدواژهها | ||
| الگوریتمهای فراابتکاری؛ بهینهسازی؛ چندهدفه؛ تکامل شورای شهر؛ جبهه پرِتو | ||
| مراجع | ||
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