Complex continuous optimization problems widely exist nowadays due to the fast development of the economy and society. Moreover, the technologies like Internet of things …
In their original versions, nature-inspired search algorithms such as evolutionary algorithms and those based on swarm intelligence, lack a mechanism to deal with the constraints of a …
Optimal power flow (OPF) problem is a large-scale, non-convex, multi-modal, and non-linear constrained optimization problem, which has been widely used in power system operation …
BC Wang, HX Li, JP Li, Y Wang - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
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 …
Over the last few decades, a number of differential evolution (DE) algorithms have been proposed with excellent performance on mathematical benchmarks. However, like any other …
Y Wang, BC Wang, HX Li… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
When solving constrained optimization problems by evolutionary algorithms, an important issue is how to balance constraints and objective function. This paper presents a new …
G Li, Q Zhang - IEEE Transactions on Evolutionary …, 2021 - ieeexplore.ieee.org
This article proposes an evolutionary algorithm using multiple penalties and multiple local surrogates (MPMLS) for expensive constrained optimization. In each generation, MPMLS …
Effective constraint handling techniques (CHTs) are of great significance for evolutionary algorithms (EAs) dealing with constrained optimization problems (COPs). To date, many …
J Wang, G Liang, J Zhang - IEEE transactions on cybernetics, 2018 - ieeexplore.ieee.org
This paper presents a cooperative differential evolution framework (CCMODE) for constrained multiobjective optimization, and two instantiations of the CCMODE framework …