بهینه‌سازی اندازه و هندسه سازه‌های خرپایی با استفاده از ترکیب روش‌های بهینه‌سازی جستجوی گرانشی و ماشین‌های یاخته‌ای

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده فنی مهندسی، دانشگاه قم، قم، ایران.

2 دانشکده فنی و مهندسی، دانشگاه ولی عصر (عج) رفسنجان، رفسنجان، ایران.

چکیده

در این مطالعه، روشی جدید جهت استفاده در حل مسائل بهینه­ سازی هندسه و اندازه در سازه ­های خرپایی با استفاده از ترکیب مؤثر روش ماشین­ های یاخته­ ای (CA) و الگوریتم جستجوی گرانشی (GSA) ارائه شده است که در ادامه به نام روش CA-GSA نام‌گذاری شده است. اساس روش GSA، قوانین گرانش نیوتنی و حرکت است. این الگوریتم به علت تأثیرگذاری مستقیم همه اجرام بر یکدیگر و عدم توجه به موضوع نخبه­ گرایی، دارای ضعف همگرایی محلی است. در این تحقیق، با کمک روش CA، اجرام در یک شبکه سلولی متناهی توزیع شده­اند و هر سلول تنها با همسایه­ های خود در ارتباط است. در روش CA-GSA، قوانین گرانش و حرکت اجرام در روش GSA به عنوان عامل ارتباط هر سلول با سلول­ های همسایه خود تعریف شده است. بنابراین، نیروی اعمال شده به هر جرم از برآیند نیروی اجرام برتر همسایه­ اش، بدست می­ آید. تعریف این اجرام همسایه و اعمال نیروی آنها به جرم مرکزی، حافظه و نخبه­ گرایی را به الگوریتم GSA افزوده است. مزیت دیگر روش جدید، به‌روزرسانی شبکه سلولی پس از هر به‌روزرسانی است که موجب می­ شود الگوریتم با تعداد آنالیزهای کمتر به مقدار بهینه اصلی دست بیابد. جهت بررسی سودمندی روش پیشنهادی و مقایسه با روش­ های CA و GSA، از سه روش CA، GSA و CA-GSA در حل چهار مسأله بهینه­ سازی هندسه و اندازه اعضای سازهای خرپایی مبنا استفاده شده است. نتایج الگوریتم توسعه داده شده در این مقاله نشان‌دهنده­ ی برتری و قدرت این الگوریتم در بهینه‌سازی هندسه و اندازه سازه ­های خرپایی نسبت به سایر روش ­های مقایسه شده در این مقاله می ­باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Sizing and Geometry Optimization of Truss Structures Using a Hybrid of Gravitational Search Algorithm and Cellular Automata

نویسندگان [English]

  • Milad Dehghani 1
  • Mostafa Mashayekhi 2
  • Mehdi Sharifi 1
1 Department of Civil Engineering, Faculty of Engineering, University of Qom,Qom, Iran
2 Department of Civil Engineering, Faculty of Technical and Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
چکیده [English]

In this study, a new method is presented to solve the geometry and sizing optimization problems of truss structures using an effective hybrid of cellular automata (CA) and gravitational search algorithm (GSA), which is named the CA-GSA method. The basic of the GSA is the Newtonian Gravity and Motion laws. Due to the direct effect of all objects on each other and the lack of attention to elitist selection, this algorithm converges to a local optimum point. In this study, with the help of the CA method, masses are distributed in a finite cellular network, and each cell is only related to its neighbors. In the CA-GSA method, the laws of gravity and motion of masses in the GSA method are defined as the relationship factor of each cell to its neighboring ones. Therefore, the applied force on each mass is obtained from the resultant force of its top neighboring masses. The definition of these top neighboring masses and their applied force on the central mass add memory and elitist selection to the GSA algorithm, respectively. Another advantage of the new method is to update the cellular network after any local evolution, which makes it possible to achieve the optimal point using fewer analyzes. To investigate the usefulness of the proposed method, the CA-GSA method was used to solve the geometry and sizing optimization problems of four benchmark truss structures. The results of CA-GSA show the superiority and power of this algorithm in comparison with the methods introduced in the literature.

کلیدواژه‌ها [English]

  • Cellular automata
  • Truss structures
  • Optimization
  • Gravitational search algorithm
  • Hybrid optimization methods
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