A comprehensive survey on NSGA-II for multi-objective optimization and applications
H Ma, Y Zhang, S Sun, T Liu, Y Shan - Artificial Intelligence Review, 2023 - Springer
In the last two decades, the fast and elitist non-dominated sorting genetic algorithm (NSGA-
II) has attracted extensive research interests, and it is still one of the hottest research …
II) has attracted extensive research interests, and it is still one of the hottest research …
A survey on evolutionary computation for complex continuous optimization
Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …
development of the economy and society. Moreover, the technologies like Internet of things …
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 …
Evolutionary multiform optimization with two-stage bidirectional knowledge transfer strategy for point cloud registration
Point cloud registration is an important task in computer vision, where the goal is to estimate
a transformation to align a pair of point clouds. Most of the existing registration methods face …
a transformation to align a pair of point clouds. Most of the existing registration methods face …
Insights on transfer optimization: Because experience is the best teacher
Traditional optimization solvers tend to start the search from scratch by assuming zero prior
knowledge about the task at hand. Generally speaking, the capabilities of solvers do not …
knowledge about the task at hand. Generally speaking, the capabilities of solvers do not …
Improving NSGA-III algorithms with information feedback models for large-scale many-objective optimization
ZM Gu, GG Wang - Future Generation Computer Systems, 2020 - Elsevier
Recently, more and more multi/many-objective algorithms have been proposed. However,
most evolutionary algorithms only focus on solving small-scale multi/many-objective …
most evolutionary algorithms only focus on solving small-scale multi/many-objective …
Multifidelity genetic transfer: an efficient framework for production optimization
Production optimization led by computing intelligence can greatly improve oilfield economic
effectiveness. However, it is confronted with huge computational challenge because of the …
effectiveness. However, it is confronted with huge computational challenge because of the …
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 two-stage evolutionary algorithm with balanced convergence and diversity for many-objective optimization
Multiobjective optimization evolutionary algorithms (MOEAs) have received significant
achievements in recent years. However, they encounter many difficulties in dealing with …
achievements in recent years. However, they encounter many difficulties in dealing with …
AnD: A many-objective evolutionary algorithm with angle-based selection and shift-based density estimation
Evolutionary many-objective optimization has been gaining increasing attention from the
evolutionary computation research community. Much effort has been devoted to addressing …
evolutionary computation research community. Much effort has been devoted to addressing …