Hybrid algorithm for global optimization based on periodic selection scheme in engineering computation
ISSN: 0264-4401
Article publication date: 5 April 2024
Issue publication date: 16 April 2024
Abstract
Purpose
Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).
Design/methodology/approach
The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.
Findings
The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.
Originality/value
This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.
Keywords
Acknowledgements
The research work described herein was also funded by the National Key Research and Development Program of China (Grant No. 2023YFC3011401), the National Natural Science Foundation of China (NSFC) (Grant No. 52090081, 52108372), the Fundamental Research Funds for the Central Universities (Grant No. 2652021016), the Open Research Fund Program of State key Laboratory of Hydroscience and Engineering (Grant No. sklhse-2023-D-01), the Young Elite Scientist Sponsorship Program by China Association for Science and Technology (Grant No. YESS20220300), the Young Elite Scientist Sponsorship Program by Beijing Association for Science and Technology (Grant No. BYESS2021126), China Postdoctoral Science Foundation (2022M723533). The financial supports are gratefully acknowledged.
Citation
Zhou, T., Wei, Y., Niu, J. and Jie, Y. (2024), "Hybrid algorithm for global optimization based on periodic selection scheme in engineering computation", Engineering Computations, Vol. 41 No. 2, pp. 385-412. https://doi.org/10.1108/EC-08-2022-0536
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited