Differential evolution with an individual-dependent mechanism Lixin Tang Yun Dong Jiyin Liu 2134/20904 https://repository.lboro.ac.uk/articles/journal_contribution/Differential_evolution_with_an_individual-dependent_mechanism/9501725 Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference of positions between individuals to perturb base vectors and thus generate new mutant individuals. However, the difference between the fitness values of individuals, which may be helpful to improve the performance of the algorithm, has not been used to tune parameters and choose mutation strategies. In this paper, we propose a novel variant of DE with an individual-dependent mechanism that includes an individual-dependent parameter (IDP) setting and an individual-dependent mutation (IDM) strategy. In the IDP setting, control parameters are set for individuals according to the differences in their fitness values. In the IDM strategy, four mutation operators with different searching characteristics are assigned to the superior and inferior individuals, respectively, at different stages of the evolution process. The performance of the proposed algorithm is then extensively evaluated on a suite of the 28 latest benchmark functions developed for the 2013 Congress on Evolutionary Computation special session. Experimental results demonstrate the algorithm's outstanding performance. 2016-04-13 11:41:04 Differential evolution (DE) Global numerical optimization Individual dependent Mutation strategy Parameter setting Information Systems Artificial Intelligence and Image Processing Business and Management not elsewhere classified