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Exploration of intelligent computing based on improved hybrid genetic algorithm

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Abstract

Aiming at the problems and shortcomings of genetic algorithm, a hybrid genetic algorithm based on chaos genetic algorithm is designed in this paper. Based on the actual situation of universities, a mathematical model of timetabling problem is proposed. In view of the deficiency of genetic algorithm, chaos is introduced into the genetic algorithm by using the inherent regularity of chaotic sequence, effectively guiding crossover and mutation operation, and avoiding the defect that standard genetic algorithm is easy to fall into local minimum. The simulation of the course scheduling problem under the same conditions is conducted at the end of the paper, with the standard genetic algorithm and hybrid genetic algorithm. By comparing the calculation results, the results proved that the hybrid genetic algorithm is fully applicable to the scheduling problem, and has a high efficiency. At last, it can be concluded that the chaos genetic algorithm provides new ideas for timetabling problem.

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Acknowledgements

This paper was supported by the Natural Science Foundation of Hubei Province of China (No. 2015CKB740).

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Authors and Affiliations

  1. School of Computer Science, Yangtze University, Jingzhou, 434023, China

    Caichang Ding, Lin Chen & Baorong Zhong

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  1. Caichang Ding
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  2. Lin Chen
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  3. Baorong Zhong
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Correspondence to Caichang Ding.

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Ding, C., Chen, L. & Zhong, B. Exploration of intelligent computing based on improved hybrid genetic algorithm. Cluster Comput 22 (Suppl 4), 9037–9045 (2019). https://doi.org/10.1007/s10586-018-2049-7

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  • DOI: https://doi.org/10.1007/s10586-018-2049-7

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