A comprehensive survey on interactive evolutionary computation in the first two decades of the 21st century
Interactive evolutionary computation (IEC) has demonstrated significant success in
addressing numerous real-world problems that are challenging to quantify mathematically or …
addressing numerous real-world problems that are challenging to quantify mathematically or …
A distance and cosine similarity-based fitness evaluation mechanism for large-scale many-objective optimization
The fitness evaluation mechanism (FEM) based on nondominated sorting may lead to slow
convergence when solving large-scale many-objective optimization problems (LSMaOPs) …
convergence when solving large-scale many-objective optimization problems (LSMaOPs) …
Reinforcement learning-based differential evolution algorithm for constrained multi-objective optimization problems
X Yu, P Xu, F Wang, X Wang - Engineering Applications of Artificial …, 2024 - Elsevier
Many real-world problems can be established as Constrained Multi-objective Optimization
Problems (CMOPs). It is still challenging to automatically set efficient parameters for …
Problems (CMOPs). It is still challenging to automatically set efficient parameters for …
[HTML][HTML] Let decision-makers direct the search for robust solutions: An interactive framework for multiobjective robust optimization under deep uncertainty
B Shavazipour, JH Kwakkel, K Miettinen - Environmental Modelling & …, 2025 - Elsevier
The robust decision-making framework (RDM) has been extended to consider multiple
objective functions and scenarios. However, the practical applications of these extensions …
objective functions and scenarios. However, the practical applications of these extensions …
Surrogate model-based optimization of methanol synthesis process for multiple objectives: A pathway towards achieving sustainable development goals
This work combines a generalized regression neural network (GRNN) with a non-dominated
sorting genetic algorithm (NSGA-II) to optimize a methanol synthesis plant for multiple …
sorting genetic algorithm (NSGA-II) to optimize a methanol synthesis plant for multiple …
A novel multi-stage multi-scenario multi-objective optimisation framework for adaptive robust decision-making under deep uncertainty
B Shavazipour, TJ Stewart - arXiv preprint arXiv:2312.11745, 2023 - arxiv.org
Many real-world decision-making problems involve multiple decision-making stages and
various objectives. Besides, most of the decisions need to be made before having complete …
various objectives. Besides, most of the decisions need to be made before having complete …
Hydrodynamic model-driven evolutionary algorithm-based operation optimization of an experimental drainage pumping station
X Li, S Xue, J Hou, Y Guo, Y Liu, H Ma… - Journal of Water and …, 2024 - iwaponline.com
The effective operation of pumping stations plays a crucial role in urban flood management.
However, challenges persist in optimizing pumping station operations, including …
However, challenges persist in optimizing pumping station operations, including …
The stacking sequence optimisation of a filament wound composite bicycle frame using the data-driven evolutionary algorithm EvoDN2
A Malá, Z Padovec, T Mareš… - Philosophical Magazine …, 2024 - Taylor & Francis
This work focusses on identifying the optimal stacking sequence for composite tubes in
mountain bike frames using a data-driven model combined with evolutionary algorithms …
mountain bike frames using a data-driven model combined with evolutionary algorithms …