[HTML][HTML] Large-scale evolutionary optimization: A review and comparative study
Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …
world applications. However, their inherent complexity, coupled with the curse of …
A general convergence analysis method for evolutionary multi-objective optimization algorithm
T Cai, H Wang - Information Sciences, 2024 - Elsevier
Convergence analysis of multi-objective optimization algorithm has been an area of vital
interest to the research community. With this regard, a number of approaches have been …
interest to the research community. With this regard, a number of approaches have been …
Approximating robust Pareto fronts by the MEOF-based multiobjective evolutionary algorithm with two-level surrogate models
The multiobjective optimization problems (MOPs) under uncertain environments are very
challenging to be solved due to the sensitivities of some robust decision variables. To find …
challenging to be solved due to the sensitivities of some robust decision variables. To find …
A population hierarchical-based evolutionary algorithm for large-scale many-objective optimization
In large-scale many-objective optimization problems (LMaOPs), the performance of
algorithms faces significant challenges as the number of objective functions and decision …
algorithms faces significant challenges as the number of objective functions and decision …
A multimodal multi-objective differential evolution with series-parallel combination and dynamic neighbor strategy
H Peng, W Xia, Z Luo, C Deng, H Wang, Z Wu - Information Sciences, 2024 - Elsevier
Multimodal multi-objective optimization problems (MMOPs), which aim to identify as many
optimal solutions as possible and exhibit multiple equivalent Pareto optimal solution sets …
optimal solutions as possible and exhibit multiple equivalent Pareto optimal solution sets …
A two-stage direction-guided evolutionary algorithm for large-scale multiobjective optimization
Large-scale multiobjective optimization problems (LSMOPs) have exponential growth in the
search space as the decision variables increase, and the vast search space poses a …
search space as the decision variables increase, and the vast search space poses a …
An improved problem transformation algorithm for large-scale multi-objective optimization
Y Sun, D Jiang - Swarm and Evolutionary Computation, 2024 - Elsevier
Abstract Solving Large-Scale Multi-Objective Optimization Problems (LSMOPs) is the major
challenge in evolution computation. Due to the large number of decision variables involved …
challenge in evolution computation. Due to the large number of decision variables involved …
A staged fuzzy evolutionary algorithm for constrained large-scale multiobjective optimization
Constrained multiobjective optimization problems (CMOPs) are prevalent in practical
applications, where constraints play a significant role. Building on techniques from …
applications, where constraints play a significant role. Building on techniques from …
[PDF][PDF] Large-ScaleMulti-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables.
L Chen, J Zhang, L Wu, X Cai… - CMES-Computer Modeling …, 2024 - cdn.techscience.cn
The large-scale multi-objective optimization algorithm (LSMOA), based on the grouping of
decision variables, is an advanced method for handling high-dimensional decision …
decision variables, is an advanced method for handling high-dimensional decision …