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مروری بر انواع الگوریتمهای فراکاوشی در بهینهسازی | ||
مدل سازی در مهندسی | ||
مقاله 3، دوره 12، شماره 38، آذر 1393، صفحه 27-43 اصل مقاله (673.57 K) | ||
شناسه دیجیتال (DOI): 10.22075/jme.2017.1677 | ||
نویسندگان | ||
حسین شریف زاده* ؛ نیما امجدی | ||
دانشگاه سمنان | ||
تاریخ دریافت: 09 بهمن 1395، تاریخ بازنگری: 27 شهریور 1396، تاریخ پذیرش: 09 بهمن 1395 | ||
چکیده | ||
با پیچیدهتر شدن مسائل بهینهسازی و عدم کارایی مطلوب روشهای تحلیلی سنتی، نیاز به ابزارهای قویتر برای حل این مسائل احساس شد. علاوهبر مشکلاتی همچون نیاز به تضمینهایی در خصوص مشتقپذیری و پیوستگی، امکان همگرایی به بهینۀ محلی، زمان حلِ این روشها در بسیاری از مسائل به صورت نمایی رشد میکند. در پاسخ به این نیاز، الگوریتمهای حل فراکاوشی ظهور پیدا کردند. این روشها هیچگونه نیازی به اطلاعات مشتق مساله ندارند، با عملگرهای خاص خود قادر به فرار از بهینۀ محلی و کشف بهینۀ کلی هستند و زمان محاسبات مورد نیاز در آنها با افزایش ابعاد مساله به صورت خطی یا چندجملهای افزایش مییابد. با اینحال بهدلیل پراکندگی این روشها در تحقیقات مختلف و عدم سازماندهی کامل آنها، محققان شناخت مناسبی از طیف گستردۀ این الگوریتمها، سازوکار و ویژگیهای این الگوریتمها ندارند. در این مقاله سعی شده است شماری از مهمترین و کاربردیترین این الگوریتمها (40 الگوریتم فراکاوشی مختلف) معرفی گردد، ویژگیهای اصلی این الگوریتمها همچون سازوکار جستجوی فضای مسالۀ بهینهسازی، عملگرهای اساسی و منبع الهام هریک شرح داده شود. همچنین بهصورت فشرده، بعضی وجوه تمایز این الگوریتمها مانند قابلیت جستجوی محلی و کلی، تعریف حافظه و تنظیم پارامترها بحث شده است. | ||
کلیدواژهها | ||
بهینهسازی؛ روشهای تحلیلی؛ الگوریتمهای فراکاوشی | ||
عنوان مقاله [English] | ||
a Review of Metaheuristic Algorithms in Optimization | ||
نویسندگان [English] | ||
Hossein Sharifzadeh؛ Nima Amjady | ||
چکیده [English] | ||
With continuously increasing complexity of optimization problems and poor performance of conventional analytical based methods, more powerful tools are required to cope these problems. Difficulties such as necessity of differentiable and continuous model as well as possibility of converging to local minimum, computational time of these methods increase exponentially as well. Metaheuristic algorithms have introduced to overcome such challenges. These methods donât require differentiation information, can discover global optimal and run away from local optima using their operators with linear or polynomial increase in their computational time. However, because of diversity and different publication resource of these methods, researchers donât know their characteristic and search mechanism well. This paper aims to introduce some of the most important of these algorithms (40 different algorithms), to describe main characteristic of these algorithms such as solution space search method, main operators and their inspiration sources. Moreover, some of unique characteristic of these algorithms such as local and global search capability, memory consideration and parameters tuning methods are discussed. | ||
کلیدواژهها [English] | ||
Optimization, Analytical methods, Metaheuristic algorithms | ||
مراجع | ||
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