Improved multi-objective differential evolution algorithm based on a decomposition strategy for multi-objective optimization problems.

ABSTRACT: Many real-world engineering problems need to balance different objectives and can be formatted as multi-objective optimization problem. An effective multi-objective algorithm can achieve a set of optimal solutions that can make a tradeoff between different objectives, which is valuable to further explore and design. In this paper, an improved multi-objective differential evolution algorithm (MOEA/D/DEM) based on a decomposition strategy is proposed to improve the performance of differential evolution algorithm for practical multi-objective nutrition decision problems. Firstly, considering the neighborhood characteristic, a neighbor intimacy factor is designed in the search process for enhancing the diversity of the population, then a new Gaussian mutation strategy with variable step size i

SUBMITTER: Fan M 

PROVIDER: S-EPMC9729643 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature