A review on evolutionary multitask optimization: Trends and challenges
Evolutionary algorithms (EAs) possess strong problem-solving abilities and have been
applied in a wide range of applications. However, they still suffer from a high computational …
applied in a wide range of applications. However, they still suffer from a high computational …
A review of population initialization techniques for evolutionary algorithms
Although various population initialization techniques have been employed in evolutionary
algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap …
algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap …
Coronavirus mask protection algorithm: A new bio-inspired optimization algorithm and its applications
Y Yuan, Q Shen, S Wang, J Ren, D Yang… - Journal of Bionic …, 2023 - Springer
Nowadays, meta-heuristic algorithms are attracting widespread interest in solving high-
dimensional nonlinear optimization problems. In this paper, a COVID-19 prevention-inspired …
dimensional nonlinear optimization problems. In this paper, a COVID-19 prevention-inspired …
Optimization of an auto drum fashioned brake using the elite opposition-based learning and chaotic k-best gravitational search strategy based grey wolf optimizer …
Y Yuan, X Mu, X Shao, J Ren, Y Zhao, Z Wang - Applied Soft Computing, 2022 - Elsevier
Highly non-linear optimization problems are widely found in many real-world engineering
applications. To tackle these problems, a novel assisted optimization strategy, named elite …
applications. To tackle these problems, a novel assisted optimization strategy, named elite …
A hybrid self-adaptive sine cosine algorithm with opposition based learning
Real-world optimization problems demand an efficient meta-heuristic algorithm which
maintains the diversity of solutions and properly exploits the search space of the problem to …
maintains the diversity of solutions and properly exploits the search space of the problem to …
Performance optimization of support vector machine with oppositional grasshopper optimization for acute appendicitis diagnosis
Preoperative differentiation of complicated and uncomplicated appendicitis is challenging.
The research goal was to construct a new intelligent diagnostic rule that is accurate, fast …
The research goal was to construct a new intelligent diagnostic rule that is accurate, fast …
An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment
R SaiSindhuTheja, GK Shyam - Applied Soft Computing, 2021 - Elsevier
Abstract Detection of Denial of Service (DoS) attack is one of the most critical issues in cloud
computing. The attack detection framework is very complex due to the nonlinear thought of …
computing. The attack detection framework is very complex due to the nonlinear thought of …
Parameters identification of solar cell models using generalized oppositional teaching learning based optimization
This paper presents a new optimization method called GOTLBO (generalized oppositional
teaching learning based optimization) to identify parameters of solar cell models. GOTLBO …
teaching learning based optimization) to identify parameters of solar cell models. GOTLBO …
Evolving chimp optimization algorithm by weighted opposition-based technique and greedy search for multimodal engineering problems
Q Bo, W Cheng, M Khishe - Applied Soft Computing, 2023 - Elsevier
This paper presents an evolved chimp optimization algorithm (ChOA) that uses greedy
search (GS) and opposition-based learning (OBL) to respectively increase the ChOA's …
search (GS) and opposition-based learning (OBL) to respectively increase the ChOA's …
Greedy opposition-based learning for chimp optimization algorithm
M Khishe - Artificial Intelligence Review, 2023 - Springer
The chimp optimization algorithm (ChOA) is a hunting-based model and can be utilized as a
set of optimization rules to tackle optimization problems. Although ChOA has shown …
set of optimization rules to tackle optimization problems. Although ChOA has shown …