Performance Comparison of Physics Based Meta-Heuristic Optimization Algorithms
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The optimization process is a process that aims to find the minimum or maximum point according to the objective function. Many different algorithms have been developed for optimization problems. While analytical methods are committed to finding the exact solution specific to their problem, heuristic methods are committed to finding the best solution to the larger set of problems. Mathematical models of the system and the objective function are needed to solve the problems. General purpose heuristic optimization algorithms are evaluated in eight different groups including physics, biology, social, herd, music, chemistry, sports and mathematics. In this study, Be about Water Cycle Algorithm, Electromagnetic Field Optimization, Big Bang Big Crunch, Gravitational Search Algorithm, Optics Inspired Optimization, the performance results of 5 different algorithms were compared for Sphere, Rastrigin, Rosenbrock, Griewank and Ackley test functions. In consequence of the number of stated population, size, run and iteration, after the minimum, maximum, standard deviation, and their mean values were established, their superiority to each other was determined.
Açıklama
International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 28-30, 2018 -- Inonu Univ, Malatya, TURKEY
Anahtar Kelimeler
Water Cycle Algorithm, Electromagnetic Field Optimization, Big Bang Big Crunch, Gravitational Search Algorithm, Optics Inspired Optimization, physics-based optimization
Kaynak
2018 International Conference on Artificial Intelligence and Data Processing (Idap)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
