Open AccessA new hybrid algorithm based on MVO and SA for function optimization
Author(s) -
Ömer Faruk Yılmaz,
Adem Alpaslan Altun,
Murat Köklü
Publication year - 2022
Publication title -
international journal of industrial engineering computations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.564
H-Index - 26
eISSN - 1923-2926
pISSN - 1923-2934
DOI - 10.5267/j.ijiec.2021.11.001
Subject(s) - simulated annealing , benchmark (surveying) , hybrid algorithm (constraint satisfaction) , algorithm , metaheuristic , optimization algorithm , computer science , mathematical optimization , mathematics , constraint logic programming , geodesy , geography , stochastic programming , constraint programming
Hybrid algorithms are widely used today to increase the performance of existing algorithms. In this paper, a new hybrid algorithm called IMVOSA that is based on multi-verse optimizer (MVO) and simulated annealing (SA) is used. In this model, a new method called the black hole selection (BHS) is proposed, in which exploration and exploitation can be increased. In the BHS method, the acceptance probability feature of the SA algorithm is used to increase exploitation by searching for the best regions found by the MVO algorithm. The proposed IMVOSA algorithm has been tested on 50 benchmark functions. The performance of IMVOSA has been compared with other latest and well-known metaheuristic algorithms. The consequences show that IMVOSA produces highly successful and competitive results.