کاربرد روش های بهبود الگوریتم بهینه‌سازی فراکاوشی برای طراحی پل‌های بتنی مسلح در مقیاس واقعی: مطالعه موردی تقاطع انهر کمربندی ارومیه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده مهندسی عمران، دانشگاه تبریز

2 مدیریت دانش موسسه عاشورا، تبریز، ایران

چکیده

یادگیری مبتنی بر تضاد (OBL) یک رویکرد موثر برای بهبود عملکرد الگوریتم‌های بهینه‌سازی فراکاوشی است که معمولا برای حل مسائل مهندسی پیچیده استفاده می‌شود. در این مقاله استراتژی یادگیری متضاد برای ترکیب با الگوریتم بهینه‌سازی ملخ (GOA) ارائه می‌شود. در این الگوریتم پیشنهادی، راه‌حل‌های تولید شده توسط الگوریتم GOA مرتب شده و به دو راه‌حل خوب و بد تقسیم می‌شوند، سپس راه‌حل‌های بد انتخاب می‌شوند تا با استفاده از آموزش برمبنای تضاد، راه حل های جدید تولید شود. برای تأیید قابلیت الگوریتم پیشنهادی، برخی از توابع ریاضیاتی معیار آزمایش شدند. علاوه بر این، عملکرد الگوریتم OGOA با اجرای یک طراحی بهینه از یک پل بتن مسلح با مقیاس واقعی ارزیابی شد. برای شناسایی پارامترهای موثر در طراحی اجزای سازه‌ای پل‌های بتن مسلح، تحلیل حساسیت انجام شده است. علاوه بر این، هزینه کل مصالح در ستون‌های پایه‌ها و عرشه پل به عنوان یک تابع هدف تعریف شد. همچنین ابعاد مقاطع و میلگردهای فولادی طولی به عنوان متغیرهای طراحی انتخاب می‌شوند. نتایج شبیه‌سازی‌ها پایداری و استحکام روش OGOA پیشنهادی را در مقایسه با GOA استاندارد نشان می‌دهد. همچنین الگوریتم پیشنهادی OGOA در طراحی بهینه ستون‌های و عرشه پل‌های بتنی مسلح یک روش کارآمد می‌باشد.

کلیدواژه‌ها


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