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Knowledge transfer in evolutionary multi-task optimization: A survey
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 …
Evolutionary multitask optimization: a methodological overview, challenges, and future research directions
In this work, we consider multitasking in the context of solving multiple optimization problems
simultaneously by conducting a single search process. The principal goal when dealing with …
simultaneously by conducting a single search process. The principal goal when dealing with …
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 …
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 …
An evolutionary multitasking memetic algorithm for multi-objective distributed heterogeneous welding flow shop scheduling
The decomposable feature of operations in the welding shop scheduling scenario results in
a vast search space, posing challenges for the design of traditional optimization algorithms …
a vast search space, posing challenges for the design of traditional optimization algorithms …
Half a dozen real-world applications of evolutionary multitasking, and more
Until recently, the potential to transfer evolved skills across distinct optimization problem
instances (or tasks) was seldom explored in evolutionary computation. The concept of …
instances (or tasks) was seldom explored in evolutionary computation. The concept of …
Evolutionary multitask optimization with lower confidence bound-based solution selection strategy
Evolutionary multitasking (EMT) is an emerging research direction within the evolutionary
computation community, attempting to concurrently solve multiple optimization tasks by …
computation community, attempting to concurrently solve multiple optimization tasks by …
Ensemble of domain adaptation-based knowledge transfer for evolutionary multitasking
Recently, a number of domain adaptation (DA) methods have been proposed for knowledge
transfer in evolutionary multitasking (EMT). However, the learned map**s in these …
transfer in evolutionary multitasking (EMT). However, the learned map**s in these …
Multiobjective multitask optimization with multiple knowledge types and transfer adaptation
Evolutionary multitasking (EMT) exploits the correlation among different tasks to help handle
them through knowledge transfer (KT) techniques in evolutionary algorithms. In this area …
them through knowledge transfer (KT) techniques in evolutionary algorithms. In this area …
Decoupling constraint: Task clone-based multi-tasking optimization for constrained multi-objective optimization
The coupling of multiple constraints can pose difficulties in solving constrained multi-
objective optimization problems (CMOPs). Existing constrained multi-objective evolutionary …
objective optimization problems (CMOPs). Existing constrained multi-objective evolutionary …