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.
(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.
Original language | English |
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Title of host publication | Proceedings of the 2016 IEEE Congress on Evolutionary Computation |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 3541-3548 |
ISBN (Print) | 978-1-5090-0622-9 |
DOIs | |
Publication status | Published - 24 Jul 2016 |
Event | 2016 IEEE Congress on Evolutionary Computation (CEC) - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016 http://www.wcci2016.org/ |
Conference
Conference | 2016 IEEE Congress on Evolutionary Computation (CEC) |
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Country/Territory | Canada |
City | Vancouver |
Period | 24/07/16 → 29/07/16 |
Internet address |