Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …

Constrained multiobjective optimization problems (CMOPs) involve both conflicting objective
functions and various constraints. Due to the presence of constraints, CMOPs' Pareto …

Constrained multiobjective optimization problems (CMOPs) are frequently encountered in
real-world applications, which usually involve constraints in both the decision and objective …

Solving constrained multiobjective optimization problems brings great challenges to an
evolutionary algorithm, since it simultaneously requires the optimization among several …

Solving constrained optimization problems (COPs) with evolutionary algorithms (EAs) is a
popular research direction due to its potential and diverse applications. One of the key …

This article presents a new constraint-handling technique (CHT), called shift-based penalty
(ShiP), for solving constrained multiobjective optimization problems. In ShiP, infeasible …

PlatEMO is an open-source platform for solving complex optimization problems, which
provides a variety of metaheuristics including evolutionary algorithms, swarm intelligence …

Evolutionary constrained multiobjective optimization has received extensive attention and
research in the past two decades, and a lot of benchmarks have been proposed to test the …

Proposing new mutation strategies to improve the optimization performance of differential
evolution (DE) is an important research study. Therefore, the main contribution of this paper …

When solving constrained optimization problems (COPs) by evolutionary algorithms, the
search algorithm plays a crucial role. In general, we expect that the search algorithm has the …