مراجعة خوارزمية المفترس البحري: التحسين المستلهم من سلوك المفترسات البحرية وتطبيقاته في مسائل الأمثلية
محتوى المقالة الرئيسي
الملخص
في السنوات الأخيرة، برزت خوارزمية المفترس البحري Marine Predator Algorithm (MPA) كأداة قوية في مجال التحسين، وهي خوارزمية مستلهمة من انواع سلوك المفترسات البحرية في البيئة الطبيعية. حيث تستند هذه الخوارزمية على استراتيجيات ثلاثة رئيسة لأجل محاكاة ما يحدث بين المفترسات والفرائس، وهذا ما يعطي توازنا قويا بين عملية الاستكشاف وعملية الاستغلال. هذه البحث محاولة لمراجعة أهم تحسينات وتعديلات وتطبيقات خوارزمـية MPA في مجالات عدة. بالمقارنة مع خوارزميات مثل (PSO) Particle Swarm Optimization) وSlime Mould Algorithm (SMA وغيرها من الخوارزمية الأخرى أثبتت MPA فعاليتها وقوتها، خاصةً في تحسين السرعة والدقة في الوصول إلى الحلول المثلى. على الرغم من نجاحاتها، تواجه MPA بعض التحديات في مشاكل معينة، مثل الحاجة إلى تعديلات إضافية لتحسين أدائها في بيئات أكثر تعقيدًا. في هذا السياق، نناقش الاتجاهات المستقبلية لتطوير هذه الخوارزمية وتوسيع نطاق استخدامها في مجالات جديدة.
التنزيلات
تفاصيل المقالة
المراجع
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