AR Jordehi - Neural Computing and Applications, 2015 - Springer
Almost all real-world optimisation problems are constrained. Solving constrained problems is difficult for optimisation techniques. In this paper, different constraint handling strategies …
The original particle swarm optimization (PSO) is not able to tackle constrained optimization problems (COPs) due to the absence of constraint handling techniques. Furthermore, most …
W Hu, GG Yen - IEEE Transactions on Evolutionary …, 2013 - ieeexplore.ieee.org
Managing convergence and diversity is essential in the design of multiobjective particle swarm optimization (MOPSO) in search of an accurate and well distributed approximation of …
Group decision making is a type of decision problem in which multiple experts acting collectively, analyze problems, evaluate alternatives, and select a solution from a collection …
Consensus is defined as a cooperative process in which a group of decision makers develops and agrees to support a decision in the best interest of the whole. It is a …
For the past many years, several constrained multiobjective evolutionary algorithms (CMOEAs) have been designed for solving constrained multiobjective optimization problems …
Differential evolution (DE) is a simple but powerful evolutionary algorithm used in multiple sciences and engineering disciplines to tackle optimization problems. DE has some …
Y Liu, Z Yang, D Xu, H Qiu, L Gao - Information Sciences, 2023 - Elsevier
Abstract Many Surrogate-Assisted Evolutionary Algorithms (SAEAs) have been developed for expensive constrained optimization problems (ECOPs) with continuous variables …
H Dong, P Wang, C Fu, B Song - Information Sciences, 2021 - Elsevier
In this paper, a novel algorithm KTLBO is presented to achieve computationally expensive constrained optimization. In KTLBO, Kriging is adopted to develop dynamically updated …