Solving multiobjective constrained trajectory optimization problem by an extended evolutionary algorithm
Highly constrained trajectory optimization problems are usually difficult to solve. Due to
some real-world requirements, a typical trajectory optimization model may need to be …
some real-world requirements, a typical trajectory optimization model may need to be …
A constrained many-objective optimization evolutionary algorithm with enhanced mating and environmental selections
Unlike the considerable research on solving many-objective optimization problems (MaOPs)
with evolutionary algorithms (EAs), there has been much less research on constrained …
with evolutionary algorithms (EAs), there has been much less research on constrained …
Approximating complex Pareto fronts with predefined normal-boundary intersection directions
Decomposition-based evolutionary algorithms using predefined reference points have
shown good performance in many-objective optimization. Unfortunately, almost all …
shown good performance in many-objective optimization. Unfortunately, almost all …
Decomposition multi-objective evolutionary optimization: From state-of-the-art to future opportunities
K Li - arXiv preprint arXiv:2108.09588, 2021 - arxiv.org
Decomposition has been the mainstream approach in the classic mathematical
programming for multi-objective optimization and multi-criterion decision-making. However …
programming for multi-objective optimization and multi-criterion decision-making. However …
Preference-inspired coevolutionary algorithm with sparse autoencoder for many-objective optimization
W Wang, S Zhang, W Song, W Ge - Soft Computing, 2023 - Springer
The function of most multi-objective algorithms (MOEAs) is to provide an overall trade-off
Pareto front to the decision makers (DMs). But DMs actually tend to have a preference for a …
Pareto front to the decision makers (DMs). But DMs actually tend to have a preference for a …
Research progress and prospect of evolutionary many-objective optimization
R Xiao, G Li, Z Chen - Control and Decision-控制与决策, 2023 - gala.gre.ac.uk
In recent years, many-objective optimization has gradually become one of the research
hotspots of multiobjective optimization. Due to the high-dimensional objective space is …
hotspots of multiobjective optimization. Due to the high-dimensional objective space is …
On the importance of isolated infeasible solutions in the many-objective constrained NSGA-III
Recently, decomposition has gained a wide interest in solving multi-objective optimization
problems involving more than three objectives also known as Many-objective Optimization …
problems involving more than three objectives also known as Many-objective Optimization …
A Survey of Decomposition-Based Evolutionary Multi-Objective Optimization: Part I-Past and Future
K Li - arXiv preprint arXiv:2404.14571, 2024 - arxiv.org
Decomposition has been the mainstream approach in classic mathematical programming for
multi-objective optimization and multi-criterion decision-making. However, it was not …
multi-objective optimization and multi-criterion decision-making. However, it was not …
Preference-inspired co-evolutionary algorithms with local PCA oriented goal vectors for many-objective optimization
Z Shu, W Wang - IEEE Access, 2018 - ieeexplore.ieee.org
It remains a challenge to identify a satisfactory set of tradeoff solutions for many-objective
optimization problems that have more than three objectives. Coevolving the solutions with …
optimization problems that have more than three objectives. Coevolving the solutions with …
约束多目标进化算法研究进展.
朱亚文， 周红标， 李杨， 徐浩渊 - Application Research of …, 2022 - search.ebscohost.com
约束多目标进化算法(CMOEAs) 能够同时处理多个相互冲突的目标函数和约束条件,
引导种群逼向可行域的最优解, 受到了研究者的广泛重视. 首先介绍了约束多目标优化问题 …
引导种群逼向可行域的最优解, 受到了研究者的广泛重视. 首先介绍了约束多目标优化问题 …