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Aug 2026
A coordinated hybrid initialization and multi-operator framework for swarm-based optimization
An enhanced sand cat swarm algorithm (ESC-SCSA) is developed and comprehensively evaluated through sensitivity analysis, ablation studies, convergence analysis, and statistical significance tests, demonstrating its effectiveness and potential generalization capability across both continuous and discrete optimization pr...
wirawati dewi ahmad, Azuraliza Abu Bakar, Mohd Nor Akmal Khalid
· Engineering Research Express · 0 citations
Aug 2026
A two-stage differential evolution algorithm for collaborative squirrel exploration and its engineering application
TSDE-SSA balances global and local search effectively, offering an efficient and stable solution for complex optimization problems with broad application potential.
Huan Chen, Yue-Hua Gao, Yuming Zhang
· Cluster Computing · 0 citations
Open access
Aug 2026
An Improved Attraction-Repulsion OptimizationAlgorithm for Global Optimization and EngineeringDesign Problems
Attraction-Repulsion Optimization Algorithm (AROA) is a recently proposed meta-heuristic algorithm known for its simplicity, ease of implementation, and robustness. However, AROA may converge to local optima when applied to complex optimization problems. To address this limitation, we propose an enhanced version called...
Fang Feng, Kuan-Ching Li, Mingjiang Cai et al.
· International Journal of Int... · 0 citations
Open access
2026
Development of a Chaotic Tent Map-Based Pelican Optimization Algorithm for Hyperparameter Optimization
Metaheuristic optimisation algorithms have received a lot of attention due to their ability to solve complicated optimisation problems without using any gradient information. However, the performance of these algorithms may be affected by insufficient exploration, premature convergence and getting stuck in local optima...
Ayeni J. A., I. W., Olanrewaju S. S.
· International journal of res... · 0 citations
Open access
Aug 2026
Chaotic Sech–Tanh dynamic opposition-based learning for metaheuristic optimization. Part I: strategy development and validation on benchmark and engineering design problems
This study proposes the Chaotic Sech-Tanh Dynamic Opposition-based Learning (CHSTDOBL) strategy, which integrates two complementary mechanisms into the dynamic opposition framework: pseudo-random sequences generated by the Ikeda chaotic map, which inject aperiodic variability to resist premature convergence, and hyperb...
M. Turgut, Mohammad Al-Rawi, O. Turgut et al.
· Kerntechnik · 0 citations
Open access
Aug 2026
Evaluating Chaotic Map Integration Strategies for MetaheuristicBased Team Formation Optimisation
The results show that CRWZOA outperforms other ZOA variants and provides the lowest cost, smallest team size with zero variance (?² = 0) and lowest execution time in comparison to other variants of the ZOA algorithm.
Kurk Wei Yi, Nurul Aisyah Aris, Raja Rina Raja Ikram et al.
· Journal of Applied Science a... · 0 citations