Knowledge transfer in evolutionary multi-task optimization: A survey
Z Tan, L Luo, J Zhong - Applied Soft Computing, 2023 - Elsevier
Evolutionary multi-task optimization (EMTO) is an optimization algorithm designed to
optimize multiple tasks simultaneously. In real life, different tasks often correlate to each …
optimize multiple tasks simultaneously. In real life, different tasks often correlate to each …
Solving nonlinear equation systems based on evolutionary multitasking with neighborhood-based speciation differential evolution
Q Gu, S Li, Z Liao - Expert Systems with Applications, 2024 - Elsevier
Locating multiple roots of nonlinear equation systems (NESs) remains a challenging and
meaningful task in the numerical optimization community. Although a large number of NES …
meaningful task in the numerical optimization community. Although a large number of NES …
What makes evolutionary multi-task optimization better: A comprehensive survey
Evolutionary multi-task optimization (EMTO) is a new branch of evolutionary algorithm (EA)
that aims to optimize multiple tasks simultaneously within a same problem and output the …
that aims to optimize multiple tasks simultaneously within a same problem and output the …
A self-adaptive evolutionary multi-task based constrained multi-objective evolutionary algorithm
Constrained multi-objective optimization problems (CMOPs) are difficult to solve since they
involve the optimization of multiple objectives and the satisfaction of various constraints …
involve the optimization of multiple objectives and the satisfaction of various constraints …
Constrained multiobjective optimization via multitasking and knowledge transfer
Solving constrained multiobjective optimization problems (CMOPs) with various features
and challenges via evolutionary algorithms is very popular. Existing methods usually adopt …
and challenges via evolutionary algorithms is very popular. Existing methods usually adopt …
Adaptive auxiliary task selection for multitasking-assisted constrained multi-objective optimization [feature]
Solving constrained multi-objective optimization problems (CMOPs) is one of the most
popular research topics in the multi-objective optimization community. Various approaches …
popular research topics in the multi-objective optimization community. Various approaches …
Evolutionary multitasking with global and local auxiliary tasks for constrained multi-objective optimization
Constrained multi-objective optimization problems (CMOPs) include the optimization of
objective functions and the satisfaction of constraint conditions, which challenge the solvers …
objective functions and the satisfaction of constraint conditions, which challenge the solvers …
Evolutionary multitasking for large-scale multiobjective optimization
Evolutionary transfer optimization (ETO) has been becoming a hot research topic in the field
of evolutionary computation, which is based on the fact that knowledge learning and transfer …
of evolutionary computation, which is based on the fact that knowledge learning and transfer …
Scaling multiobjective evolution to large data with minions: A Bayes-informed multitask approach
In an era of pervasive digitalization, the growing volume and variety of data streams poses a
new challenge to the efficient running of data-driven optimization algorithms. Targeting …
new challenge to the efficient running of data-driven optimization algorithms. Targeting …
Domain adaptation multitask optimization
Multitask optimization (MTO) is a new optimization paradigm that leverages useful
information contained in multiple tasks to help solve each other. It attracts increasing …
information contained in multiple tasks to help solve each other. It attracts increasing …