چکیده مقاله
Evolutionary algorithms such as PSO, ICA, GA and etc These algorithms are taken from biological or social evolutionary methods Such algorithms for optimization problems with a large scale of nonlinear variables are more appropriate than traditional methods Traditional methods often rely on the computational power of the computer and did not use smart techniques and most of these methods failed to solve nonlinear problems with a large number of variables In this paper, 10 mathematical benchmark functions are compared with 7 methods of meta heuristic optimization algorithms Algorithms such as PSO, ICA, GA A brief description of each of the algorithms is presented and these algorithms are compared with different functions of the benchmark and with a large number of variables large scale in terms of computational time and convergence rate of the answers Based on these analyses and comparisons, it will be determined which of these algorithms will be improved with which operators
کلیدواژهها
نویسندگان
Hossein behniaasl
Simulation and Optimization Vehicle Design Research Lab, School of Automotive Engineering, Iran University of Science and Technology, Tehran, Iran
Majid Kheybari
Vehicle Dynamical Systems Research Lab, School of Automotive Engineering, Iran University of Science and Technology, Tehran, Iran
شیوه ارجاع
behniaasl, Hossein and Kheybari, Majid,1397,Comparison among seven meta-heuristic algorithms for optimizing ten benchmark mathematical functions with large-scale,International Conference on Interdisciplinary Studies in Electrical, Computer, Mechanical and Mechatronics Engineering in Iran and the Islamic World,Karaj
ارائهشده در
مجموعه مقالات کنفرانس بین المللی تحقیقات بین رشته ای در مهندسی برق، کامپیوتر، مکانیک و مکاترونیک در ایران و جهان اسلام31 شهریور 1397 · کرج