Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …

Dynamic constrained optimization problems (DCOPs) are difficult to solve because both
objective function and constraints can vary with time. Although DCOPs have drawn attention …

Dynamic constrained optimization problems (DCOPs) are common and important
optimization problems in real-world, which have great difficulty to solve. Dynamic …

Recently, several researchers within the evolutionary and swarm computing community
have been interested in solving dynamic multi-objective problems where the objective …

Dynamic optimization, for which the objective functions change over time, has attracted
intensive investigations due to the inherent uncertainty associated with many real-world …

Repair methods, which usually require feasible solutions as reference, have been employed
by Evolutionary Algorithms to solve constrained optimization problems. In this work, a novel …

Dynamic constrained optimization problems have received increasing attention in recent
years. We study differential evolution which is one of the high performing class of algorithms …

An empirical study of the algorithm dynamic differential evolution with combined variants
with a repair method (DDECV++ Repair) in the solution of dynamic constrained optimization …

Dynamic constrained optimisation problems (DCOPs) have specific characteristics that do
not exist in dynamic optimisation problems with bounded constraints or without constraints …

An algorithm inspired in two differential evolution variants is proposed to solve Dynamic
Constrained Optimization Problems (DCOPs). It is also added a repair method based on the …