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Integration of Models of Adaptive Behavior of Ant and Bee Colony

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 764)

Abstract

The paradigm of the swarm algorithm is proposed on the basis of integration of models of adaptive behavior of ant and bee colony. Integration of models is reduced to the creation of a hybrid agent alternately performing the functions of adaptive behavior of ant and bee colony. The proposed class of hybrid algorithms can be used to solve a wide range of combinatorial problems Based on the hybrid paradigm, a partitioning algorithm has been developed. Also article give a comparison hybrid algorithms with other methods of solution problem. Compared with the existing algorithms, the improvement of results is achieved by 5–10%. The probability of obtaining the global optimum was 0.9.

Keywords

  • Swarm intelligence
  • Adaptive behavior
  • Ant and Bee Colony
  • Hybrid algorithm
  • Optimization

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Acknowledgements

This research is supported by grants of the Russian Foundation for Basic Research of the Russian Federation, the project № 18-07-00737.

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Correspondence to Oleg B. Lebedev .

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Lebedev, B.K., Lebedev, O.B., Lebedeva, E.M., Kostyuk, A.I. (2019). Integration of Models of Adaptive Behavior of Ant and Bee Colony. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_18

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