Mutigroup-Based Phasmatodea Population Evolution Algorithm with Mutistrategy for IoT Electric Bus Scheduling. (31st January 2022)

• Record Type: Journal Article
• Authors: Zhu, Yunxiang; Yan, Fengting; Pan, Jeng-Shyang; Yu, Lei; Bai, Yuanfei; Wang, Weigang; He, Chunxia; Shi, Zhicai
• Other Names: Hwang Feng-Jang Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2022(2022)
• Publication Date: 2022-01-31
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2022/1500646
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : The Phasmatodea population evolution algorithm (PPE) is a novel metaheuristic algorithm proposed in recent years, which simulates the evolutionary trend of stick insect population. In this article, a multigroup-based Phasmatodea population evolution algorithm with mutistrategy (MPPE) is proposed to further improve the overall performance of PPE. During the initialization period, the stick insect population is divided into multiple groups, and the step factor of the flower pollen algorithm is introduced into the population growth model of no more than half of the groups. This makes the population evolution trend diversified and prevents the algorithm from falling into the local optimal solution to a certain extent. In terms of intergroup communication, two communication strategies are adopted to mutate and replace the inferior particles, respectively, which improves the convergence speed and search ability of the algorithm. In the MPPE performance test, we compared it with PPE, five standard algorithms, and other parallel algorithms in CEC 2013 Benchmark Suite. Finally, this algorithm is applied to the IoT based electric bus scheduling for urban waterlogging situation, and the excellent performance of MPPE is verified comprehensively.