A dynamic multi-objective optimization evolutionary algorithm based on hybrid initialization and ensemble model prediction strategy

A multi-strategy enhanced chaotic evolution algorithm for global optimization and engineering applications

A dynamic multi-objective optimization evolutionary algorithm based on decision variable classification and multi-stage prediction model

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...

Differential evolution with fitness-based mutation strategy and diversity enhancement mechanism for numerical optimization

The experimental results show that FMDM-DE demonstrates superiority or strong competitiveness over seven state-of-the-art algorithms in terms of mean squared error, standard deviation, and optimization accuracy, indicating its excellent robustness and optimization capability.

A Hybrid Particle Swarm Optimization and Differential Evolution Algorithm with Adaptive Population and Dynamic Parameter Allocation

Traditional particle swarm optimization (PSO) easily falls into premature convergence, while differential evolution (DE) is highly sensitive to fixed control parameters. Existing PSO-DE hybrid frameworks suffer from static population sizes and insufficient cross-population information exchange. This paper proposes PSO-...

An Evolution Algorithm with Objective-Wise Variable Analysis for Sparse Large-Scale Multi-Objective Optimization

An objective-wise variable analysis method that first evaluates the sensitivity of each objective to all decision variables, and then comprehensively aggregates the sensitivity information across multiple objectives to estimate the overall importance of decision variables is proposed.