Titlebook: Intelligence Computation and Applications; 14th International S Kangshun Li,Yong Liu Conference proceedings 2024 The Editor(s) (if applicab

祖传

Improved Particle Swarm Algorithm Using Multiple Strategiesved particle swarm optimization algorithms proposed by previous researchers. Based on this analysis, a modified algorithm for particle swarm optimization is proposed. The enhanced algorithm adjusts the inertia weight parameter in a nonlinear manner and dynamically changes the self-learning factor us

捏造

A Reference Vector Guided Evolutionary Algorithm with Diversity and Convergence Enhancement Strategie scenarios. Reference-vector-guided selection is an exemplary method for decomposition-based many-objective evolutionary algorithms (MaOEAs). Aiming at solving or alleviating the defects reference vector guided selection confronts, this paper proposes a reference vector guided evolutionary algorith

Crepitus

Research on Mine Emergency Evacuation Scheme Based on Dynamic Multi-objective Evolutionary Algorithmat significance for reducing casualties and ensuring life safety. Therefore, this paper first establishes a mine emergency evacuation model, and then proposes a dynamic single-objective evolutionary algorithm to optimize the model. This algorithm can adapt to the optimization of emergency evacuation

受辱

An Adaptive Dynamic Parameter Multi-objective Optimization Algorithmynamic parameter multi-objective optimization algorithm is proposed (ADPMO). The new algorithm consists of three main strategies. Firstly, a new mutation method based on individual competition mechanism integrated with k-means clustering is proposed, which updates the velocity and position informati

Amenable

Adaptive Elimination Particle Swarm Optimization Algorithm for Logistics Schedulingems. For the logistics scheduling problem, in the face of complex, large-scale search solution space will consume many resources. The standard particle swarm optimization can falling into local optimum easily when facing more complex problems. In this paper, three optimization strategies are designe

Inelasticity

A Modified Two_Arch2 Based on Reference Points for Many-Objective Optimizationnce of most multi-objective evolutionary algorithms (MOEAs) often deteriorates because it is hardly to achieve a balance between convergence and population diversity. To address this issue, this paper proposes a modified Two_Arch2 based on reference points (called Two_Arch2-RP). Firstly, a simplifie

ARCH

细微差别

A Multi-population Hierarchical Differential Evolution for Feature Selectionof selecting features is an optimization problem and prone to getting trapped in local optima, FS methods based on evolutionary computation (EC) can effectively tackle such problems. Therefore, this paper proposes a multi-population hierarchical differential evolution (MPDE) to solve the FS problem.

Iniquitous

Research on State-Owned Assets Portfolio Investment Strategy Based on Improved Differential Evolutioon, so the effective solution has become a hot issue. Differential evolution algorithm has some disadvantages, such as slow convergence speed and easy to fall into local optimal solution. In this paper, a new differential evolution algorithm based on cluster analysis is proposed. The improved algori

Nonthreatening