Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/57049
Title: SHuffled Ant Lion Optimization approach with an exponentially weighted random walk strategy
Authors: Durgut, P.G.
Tozak, M.B.
Ayvaz, M.T.
Keywords: Ant Lion Optimization (ALO); Boundary shrinking procedure; SHALO; Shuffling
Biomimetics; Genetic algorithms; Ant lion optimization; Boundary shrinking procedure; Condition; Optimisations; Optimization approach; Optimization method; Random walk strategies; Shuffled ant lion optimization; Shuffling; Particle swarm optimization (PSO)
Publisher: Springer Science and Business Media Deutschland GmbH
Abstract: Ant Lion Optimization (ALO) method is one of the population-based nature-inspired optimization algorithms which mimics the hunting strategy of antlions. ALO is successfully employed for solving many complicated optimization problems. However, it is reported in the literature that the original ALO has some limitations such as the requirement of high number of iterations and possibility of trapping to local optimum solutions, especially for complex or large-scale problems. For this purpose, the SHuffled Ant Lion Optimization (SHALO) approach is proposed by conducting two improvements in the original ALO. Performance of the proposed SHALO approach is evaluated by solving some unconstrained and constrained problems for different conditions. Furthermore, the identified results are statistically compared with the ones obtained by using the original ALO, two improved ALOs which are the self-adaptive ALO (saALO) and the exponentially weighted ALO (EALO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) approaches. Identified results indicated that the proposed SHALO approach significantly improves the solution accuracy with a mean success rate of 76% in terms of finding the global or near-global optimum solutions and provides better results than ALO (22%), saALO (25%), EALO (14%), GA (28%), and PSO (49%) approaches for the same conditions. © The Author(s) 2024.
URI: https://doi.org/10.1007/s00521-024-09566-5
https://hdl.handle.net/11499/57049
ISSN: 0941-0643
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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