1
Electrical and Electronic Engineering, Shiraz University of Technology
2
Mechanical and Aerospace Engineering, Shiraz University of Technology
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.
Badjian, H., Zare, S., & Tavakolpour-Saleh, A. (2017). Multi-objective Optimization of Stirling Heat Engine Using Gray Wolf Optimization Algorithm (TECHNICAL NOTE). International Journal of Engineering, 30(6), 895-903.
MLA
Hamed Badjian; Shahryar Zare; Alireza Tavakolpour-Saleh. "Multi-objective Optimization of Stirling Heat Engine Using Gray Wolf Optimization Algorithm (TECHNICAL NOTE)". International Journal of Engineering, 30, 6, 2017, 895-903.
HARVARD
Badjian, H., Zare, S., Tavakolpour-Saleh, A. (2017). 'Multi-objective Optimization of Stirling Heat Engine Using Gray Wolf Optimization Algorithm (TECHNICAL NOTE)', International Journal of Engineering, 30(6), pp. 895-903.
VANCOUVER
Badjian, H., Zare, S., Tavakolpour-Saleh, A. Multi-objective Optimization of Stirling Heat Engine Using Gray Wolf Optimization Algorithm (TECHNICAL NOTE). International Journal of Engineering, 2017; 30(6): 895-903.
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