Performance Comparison of Physics Based Meta-Heuristic Optimization Algorithms

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dc.authoridOztemiz, Furkan/0000-0001-5425-3474
dc.authoridDemirol, Doygun/0000-0002-3272-1078
dc.authoridKarci, Ali/0000-0002-8489-8617
dc.authorwosidKARCI, Ali/A-9604-2019
dc.authorwosidOztemiz, Furkan/KOD-2246-2024
dc.authorwosidDemirol, Doygun/Y-5712-2018
dc.authorwosidDemirol, Doygun/AFO-7032-2022
dc.authorwosidKarci, Ali/AAG-5337-2019
dc.contributor.authorDemirol, Doygun
dc.contributor.authorOztemiz, Furkan
dc.contributor.authorKarci, Ali
dc.date.accessioned2024-08-04T20:45:45Z
dc.date.available2024-08-04T20:45:45Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.descriptionInternational Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 28-30, 2018 -- Inonu Univ, Malatya, TURKEYen_US
dc.description.abstractThe 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.en_US
dc.description.sponsorshipInonu Univ, Comp Sci Dept,IEEE Turkey Sect,Anatolian Scien_US
dc.identifier.isbn978-1-5386-6878-8
dc.identifier.scopus2-s2.0-85062491028en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11616/98676
dc.identifier.wosWOS:000458717400023en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2018 International Conference on Artificial Intelligence and Data Processing (Idap)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectWater Cycle Algorithmen_US
dc.subjectElectromagnetic Field Optimizationen_US
dc.subjectBig Bang Big Crunchen_US
dc.subjectGravitational Search Algorithmen_US
dc.subjectOptics Inspired Optimizationen_US
dc.subjectphysics-based optimizationen_US
dc.titlePerformance Comparison of Physics Based Meta-Heuristic Optimization Algorithmsen_US
dc.typeConference Objecten_US

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