Omidvar, MN orcid.org/0000-0003-1944-4624, Kazimipour, B, Li, X et al. (1 more author) (2016) CBCC3 — A contribution-based cooperative co-evolutionary algorithm with improved exploration/exploitation balance. In: 2016 IEEE Congress on Evolutionary Computation (CEC). 2016 IEEE Congress on Evolutionary Computation (CEC), 24-29 Jul 2016, Vancouver BC, Canada. IEEE , pp. 3541-3548. ISBN 978-1-5090-0623-6
Abstract
Cooperative Co-evolution (CC) is a promising framework for solving large-scale optimization problems. However, the round-robin strategy of CC is not an efficient way of allocating the available computational resources to components of imbalanced functions. The imbalance problem happens when the components of a partially separable function have non-uniform contributions to the overall objective value. Contribution-Based Cooperative Co-evolution (CBCC) is a variant of CC that allocates the available computational resources to the individual components based on their contributions. CBCC variants (CBCC1 and CBCC2) have shown better performance than the standard CC in a variety of cases. In this paper, we show that over-exploration and over-exploitation are two major sources of performance loss in the existing CBCC variants. On that basis, we propose a new contribution-based algorithm that maintains a better balance between exploration and exploitation. The empirical results show that the new algorithm is superior to its predecessors as well as the standard CC.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Accounting & Finance Division (LUBS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 31 Jan 2020 11:10 |
Last Modified: | 14 Feb 2020 12:18 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/cec.2016.7744238 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156237 |