Evolutionary multi-task optimization (EMTO) is an optimization algorithm designed to
optimize multiple tasks simultaneously. In real life, different tasks often correlate to each …

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 …

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 …

Constrained multi-objective optimization problems (CMOPs) are difficult to solve since they
involve the optimization of multiple objectives and the satisfaction of various constraints …

Solving constrained multiobjective optimization problems (CMOPs) with various features
and challenges via evolutionary algorithms is very popular. Existing methods usually adopt …

Handling conflicting objectives and finding multiple Pareto optimal solutions are two
challenging issues in solving multiobjective optimization problems (MOPs). Inspired by the …

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 …

Constrained multi-objective optimization problems (CMOPs) include the optimization of
objective functions and the satisfaction of constraint conditions, which challenge the solvers …

Solving constrained multi-objective optimization problems (CMOPs) is one of the most
popular research topics in the multi-objective optimization community. Various approaches …

Evolutionary multitasking (EMT) is an emerging research direction within the evolutionary
computation community, attempting to concurrently solve multiple optimization tasks by …