Differential Evolution with an Individual-Dependent Mechanism accepted - repository.pdf (1.2 MB)

Differential evolution with an individual-dependent mechanism

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journal contribution
posted on 13.04.2016 by Lixin Tang, Yun Dong, Jiyin Liu
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.

History

School

  • Business and Economics

Department

  • Business

Published in

IEEE Transactions on Evolutionary Computation

Volume

19

Issue

4

Pages

560 - 574

Citation

TANG, L., DONG, Y. and LIU, J., 2015. Differential evolution with an individual-dependent mechanism. IEEE Transactions on Evolutionary Computation, 19 (4), pp.560-574.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

ISSN

1089-778X

Language

en

Exports