نوع مقاله: مقاله پژوهشی

نویسندگان

1 عضو هیات علمی گروه مهندسی عمران، دانشگاه بزرگمهر قائنات

2 استادیار گروه مهندسی مکانیک، دانشکده فنی مهندسی، دانشگاه بزرگمهر قائنات

چکیده

مقاله حاضر به ارائه یک روش جدید بهینه‌سازی ترکیبی با استفاده از ترکیب دو الگوریتم بهینه‌سازی برخورد دینامیکی اجسام و الگوریتم ژنتیک (GMCBO) می‌پردازد. یکی از نقاط ضعف الگوریتم برخورد دینامیکی اجسام، افتادن در دام بهینه محلی و عدم رسیدن به بهینه سراسری است. برای رفع این نقطه‌ضعف، در این پژوهش ابتدا اصلاحاتی بر روی فرایند الگوریتم برخورد دینامیکی اجسام انجام‌گرفته و سپس استفاده از اعمال بعضی از مفاهیم الگوریتم ژنتیک در طی مراحل فرایند بهینه‌سازی، علاوه بر بالا بردن سرعت همگرایی، باعث افزایش قدرت یافتن جواب بهینه سراسری و فرار از دام بهینه محلی می‌شود. برای ارزیابی چگونگی عملکرد روش ارائه‌شده، به طراحی بهینه چندین سازه خرپای استاندارد پرداخته‌شده است. مقایسه نتایج تحلیل سازه‌ها به کمک روش GMCBO با دیگر روش‌های بهینه‌سازی نشان‌دهنده سرعت بالای همگرایی الگوریتم پیشنهادی و قدرت آن در یافتن جواب بهینه سراسری مسئله است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A hybrid genetic modified colliding bodies optimization algorithm for design of structures with multi loads

نویسندگان [English]

  • M Arjmand 1
  • M Sheikhi Azqandi 2

1 Department of Civil Engineering, Bozorgmehr University of Qaenat, qaen, Iran

2 Mechanical Engineering, Bozorgmehr university of Qaenat, Qaen, Iran

چکیده [English]

This paper presents a new hybrid optimization method with combining colliding bodies optimization (CBO) and genetic algorithm (GMCBO). One of the weaknesses of colliding bodies optimization is falling into the trap of local optimal and not finding of global optima. In this paper, to overcome this weak point, at first, some modifications are done on CBO process and then by using the concept of genetic algorithm able to enhance of convergence rate, increasing power of finding global optimal design and escaping of local optimal. For evaluating the performance of the proposed method, the optimal design of several benchmark truss structures has been discussed. Compare the results of the structural analysis with GMCBO and other optimization methods such as colliding bodies optimization, genetic algorithm, harmony search, and heuristic particle swarm optimization method shows high convergence rate and its ability to find the global optimal solution of the proposed algorithm for structural optimization problems.

کلیدواژه‌ها [English]

  • Colliding Body
  • genetic algorithm
  • Discrete Variable
  • Multi loads

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