A survey of multi-objective optimization methods and their applications for nuclear scientists and engineers
Problems in nuclear engineering–such as reactor core design–involve a multitude of design
variables including fuel or assembly configurations; all of which require careful …
variables including fuel or assembly configurations; all of which require careful …
A survey on learnable evolutionary algorithms for scalable multiobjective optimization
Recent decades have witnessed great advancements in multiobjective evolutionary
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
A dividing-based many-objective evolutionary algorithm for large-scale feature selection
Feature selection is a critical preprocess for constructing model in computer vision and
machine learning, yet it is difficult to simultaneously satisfy both reducing features' number …
machine learning, yet it is difficult to simultaneously satisfy both reducing features' number …
Objective reduction in many-objective optimization: evolutionary multiobjective approaches and comprehensive analysis
Many-objective optimization problems bring great difficulties to the existing multiobjective
evolutionary algorithms, in terms of selection operators, computational cost, visualization of …
evolutionary algorithms, in terms of selection operators, computational cost, visualization of …
A new preference disaggregation TOPSIS approach applied to sort corporate bonds based on financial statements and expert's assessment
DF de Lima Silva, L Ferreira… - Expert systems with …, 2020 - Elsevier
This paper presents a new version of the TOPSIS method for sorting problems. The
proposed method, called Preference Disaggregation on Technique for Order of Preference …
proposed method, called Preference Disaggregation on Technique for Order of Preference …
A survey of decomposition based evolutionary algorithms for many-objective optimization problems
X Guo - IEEE Access, 2022 - ieeexplore.ieee.org
The framework of decomposition-based multi-objective evolutionary algorithms (MOEA/D)
has evolved for more than ten years, and it has become irreplaceable tool for solving multi …
has evolved for more than ten years, and it has become irreplaceable tool for solving multi …
Entropy-based termination criterion for multiobjective evolutionary algorithms
Multiobjective evolutionary algorithms evolve a population of solutions through successive
generations toward the Pareto-optimal front (POF). One of the most critical questions faced …
generations toward the Pareto-optimal front (POF). One of the most critical questions faced …
Dimensionality reduction for multi-criteria problems: An application to the decommissioning of oil and gas installations
ID Martins, L Bahiense, CED Infante… - Expert Systems with …, 2020 - Elsevier
This paper is motivated by decommissioning studies in the field of oil and gas, which
comprise a very large number of installations and are of interest to a large number of …
comprise a very large number of installations and are of interest to a large number of …
[HTML][HTML] Assisting decision-makers select multi-dimensionally efficient infrastructure designs–Application to urban drainage systems
Multi-objective design approaches can help identify future infrastructure system designs that
appropriately balance different engineering, environmental, and other societal goals …
appropriately balance different engineering, environmental, and other societal goals …
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 …