Abstract
The phasmatodea population evolution algorithm (PPE) is a novel algorithm to simulate population evolution. In this paper, a multi-strategy parallel phasmatodea population evolution algorithm (MPPPE) is proposed to further improve the comprehensive performance of PPE. The step factor of the flower pollination algorithm is introduced to maintain the diversity of population. In terms of communication, two communication strategies are adopted, which not only speeds up the convergence rate but also improves the exploration ability of the algorithm. We compared this algorithm with the other three optimization algorithms in the CEC2013 test function and proved the excellent performance of this algorithm. Finally, this algorithm is applied to the bus scheduling problem in traffic transportation, and satisfactory optimization results are obtained.
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Acknowledgements
The authors are grateful for the financial support received from the National Key Project of China (No. 2020AAA0109300), the Open Research Project of Shanghai Key Laboratory of Information Security Integrated Management Technology (No. AGK2019004), and the Research on Intelligent Scheduling of Urban Waterlogging Emergency Facilities Based on Multi-source Information (No. 21511103704).
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Zhu, Y., Yan, F., Pan, JS., Wan, W., Huang, B., Shi, Z. (2022). Multi-strategy Parallel Phasmatodea Population Evolution Algorithm for Public Transport Scheduling. In: Pan, JS., Meng, Z., Li, J., Virvou, M. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 278. Springer, Singapore. https://doi.org/10.1007/978-981-19-1053-1_21
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