Abstract
In the paper several extensions of a successful EDA-type algorithm, namely \(COMMA_{op}\), inspired by the paradigm of agent-based computing (EMAS) are presented. The proposed algorithms leveraging notions connected with EMAS, such as reproduction and death, or even the population decomposition, turn out to be better than the original algorithm. The evidence for this is presented in the end of the paper, utilizing QAP problems by Éric Taillard as benchmarks.
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This research was supported by AGH University of Science and Technology Statutory Fund.
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Byrski, A., Kisiel-Dorohinicki, M., Tusiński, N. (2017). Extending Estimation of Distribution Algorithms with Agent-Based Computing Inspirations. In: Mercik, J. (eds) Transactions on Computational Collective Intelligence XXVII. Lecture Notes in Computer Science(), vol 10480. Springer, Cham. https://doi.org/10.1007/978-3-319-70647-4_13
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