Abstract
The paper considers a problem of building the hybrid algorithm for solving the optimization design tasks on the basis of integration of different methods of computation intelligence. The authors describe the definition and the main approaches to building the hybrid systems and demonstrate the possibilities of integration of the evolutionary design and multi-agent systems methods The different approaches to evolutionary design of the agents are considered. Different methods of parallelizing the computational process and the main models of parallel genetic algorithms, their benefits and shortcomings are described and analyzed in the paper. A hybrid parallel genetic algorithm for searching and optimization of the design decisions is developed in the paper. The algorithm is implemented as software subsystem and investigated in terms of its effectiveness.
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This research is supported by the grant from the Russian Foundation for Basic Research (projects 17-01-00627).
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Gladkov, L.A., Gladkova, N.V., Semushin, E.Y. (2020). Parallel Hybrid Genetic Algorithm for Solving Design and Optimization Problems. In: Hu, Z., Petoukhov, S., He, M. (eds) Advances in Intelligent Systems, Computer Science and Digital Economics. CSDEIS 2019. Advances in Intelligent Systems and Computing, vol 1127. Springer, Cham. https://doi.org/10.1007/978-3-030-39216-1_23
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DOI: https://doi.org/10.1007/978-3-030-39216-1_23
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