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In this paper, we propose an improved optimization algorithm that uses the benefits of multiple deferential evolution operators.
The performance of the proposed algorithm is tested by solving 57 real-world constrained problems with different dimensions, number of equality and equality.
In this paper, we propose an improved optimization algorithm that uses the benefits of multiple deferential evolution operators, with the best one is emphasized ...
This paper presents a multi-populated differential evolution algorithm to solve real-parameter constrained optimization problems.
The performance of the proposed algorithm is tested by solving 10 problems with 5, 10, 15 and 20 dimensions taken from CEC2020 competition on single objective ...
Dec 30, 2020 · A multi-operator DE algorithm is developed, which uses a landscape-based indicator to choose the best-performing DE operator throughout the evolutionary ...
Jul 1, 2020 · An improved optimization algorithm is proposed that uses the benefits of multiple differential evolution operators, with more emphasis ...
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Dec 7, 2022 · In this paper, an improved multi-objective differential evolution algorithm (MOEA/D/DEM) based on a decomposition strategy is proposed to improve the ...
This paper introduces a DE algorithm framework that uses multiple search operators in each generation, so that the appropriate mix of the search operators, ...
IMODE is modified to make it suitable for solving constrained problems, leading to a new algorithm termed Constrained Multi-Operator Differential Evolution ( ...