IJE TRANSACTIONS C: Aspects Vol. 30, No. 6 (June 2017) 895-903    Article in Press

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A. R. Tavakolpour-Saleh, SH. Zare and H. Badjian
( Received: February 11, 2017 – Accepted in Revised Form: April 21, 2017 )

Abstract    The use of meta-heuristic optimization methods have become quite generic in the past two decades. This paper provides a theoretical investigation to find optimum design parameters of the Stirling heat engines using a recently presented nature-inspired method namely the gray wolf optimization (GWO). This algorithm is utilized for the maximization of the output power/thermal efficiency as well as minimization of the pressure loss. The linear programming technique is employed for analyzing the multi-objective problem and the result is compared with the three individually computed costs of the aforementioned cost functions. The results show that the new meta-heuristic algorithm (i.e. GWO) yields acceptable results in quality compared to the other presented methods such as TOPSIS and Bellman-Zadeh.


Keywords    Stirling engine, power output, pressure loss, thermal efficiency, gray wolf optimizer,multi-objective optimization, linear programming technique


چکیده    استفاده از روشهای بهینهسازی فراابتکاری در دو دهه گذشته بسیار فراگیر شده است. در این مقاله یک تحقیق نظری برای پیدا کردن پارامترهای طراحی بهینه موتورهای حرارتی استرلینگ، با استفاده از روشی الهام گرفته از طبیعت که به تازگی ارائه شده است، یعنی بهینهسازی گرگ خاکستری (GWO)، صورت گرفته است. این الگوریتم برای به حداکثر رساندن قدرت خروجی، بازده حرارتی و همچنین به حداقل رساندن افت فشار استفاده شده است. در این مقاله، تکنیک خطیسازی برای تحلیل مساله چندهدفه به کار گرفته شده است. به عبارت دیگر، به کمک سه تابع هدف به صورت جداگانه و به کمک تکنیک خطیسازی، مساله حاوی سه تابع هدف به صورت همزمان حل شده است . نتایج نشان میدهد که الگوریتم گرگهای خاکستری استفاده شده در این مقاله، خروجی قابل قبولی از لحاظ کیفیت در مقایسه به سایر روشهای مطرح همچون TOPSIS و Bellman-Zadeh دارد.


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