Multi-strategy multi-objective differential evolutionary algorithm with reinforcement learning
Multiobjective evolutionary algorithms (MOEAs) have gained much attention due to their
high effectiveness and efficiency in solving multiobjective optimization problems (MOPs) …
high effectiveness and efficiency in solving multiobjective optimization problems (MOPs) …
Learning unified mutation operator for differential evolution by natural evolution strategies
Differential evolution (DE) is one of the widely studied algorithms in evolutionary
computation. Recently, many adaptive mechanisms have been proposed for DE including …
computation. Recently, many adaptive mechanisms have been proposed for DE including …
Learning adaptive differential evolution by natural evolution strategies
Adaptive parameter control is critical in the design and application of evolutionary algorithm
(EA), so does in differential evolution. In the past decade, many adaptive evolutionary …
(EA), so does in differential evolution. In the past decade, many adaptive evolutionary …
Local optima correlation assisted adaptive operator selection
For solving combinatorial optimisation problems with metaheuristics, different search
operators are applied for sampling new solutions in the neighbourhood of a given solution. It …
operators are applied for sampling new solutions in the neighbourhood of a given solution. It …
Variational reinforcement learning for hyper-parameter tuning of adaptive evolutionary algorithm
The performance of an evolutionary algorithm (EA) is deeply affected by its control
parameter's setting. It has become a trend in recent studies to treat the control parameter as …
parameter's setting. It has become a trend in recent studies to treat the control parameter as …
Learning to Transfer for Evolutionary Multitasking
Evolutionary multitasking (EMT) is an emerging approach for solving multitask optimization
problems (MTOPs) and has garnered considerable research interest. The implicit EMT is a …
problems (MTOPs) and has garnered considerable research interest. The implicit EMT is a …
An investigation of adaptive operator selection in solving complex vehicle routing problem
Search operators play an important role in meta-heuristics. There are typically a variety of
search operators available for solving a problem, and the selection and order of using the …
search operators available for solving a problem, and the selection and order of using the …
Learning to select the recombination operator for derivative-free optimization
Extensive studies on selecting recombination operators adaptively, namely, adaptive
operator selection (AOS), during the search process of an evolutionary algorithm (EA), have …
operator selection (AOS), during the search process of an evolutionary algorithm (EA), have …