Monkey King Evolution: an enhanced ebb-tide-fish algorithm for global optimization and its application in vehicle navigation under wireless sensor network environment

Jeng-Shyang Pan, Zhenyu Meng, Shu-Chuan Chu, Hua-Rong Xu

    Research output: Contribution to journalArticlepeer-review

    23 Citations (Scopus)

    Abstract

    Optimization algorithms are proposed to maximize the desirable properties while simultaneously minimizing the undesirable characteristics. Particle Swarm Optimization (PSO) is a famous optimization algorithm, and it has undergone many variants since its inception in 1995. Though different topologies and relations among particles are used in some state-of-the-art PSO variants, the overall performance on high dimensional multimodal optimization problem is still not very good. In this paper, we present a new memetic optimization algorithm, named Monkey King Evolutionary (MKE) algorithm, and give a comparative view of the PSO variants, including the canonical PSO, Inertia Weighted PSO, Constriction Coefficients PSO, Fully-Informed Particle Sawrm, Cooperative PSO, Comprehensive Learning PSO and some variants proposed in recent years, such as Dynamic Neighborhood Learning PSO, Social Learning Particle Swarm Optimization etc. The proposed MKE algorithm is a further work of ebb-tide-fish algorithm and what’s more it performs very well not only on unimodal benchmark functions but also on multimodal ones on high dimensions. Comparison results under CEC2013 test suite for real parameter optimization show that the proposed MKE algorithm outperforms state-of-the-art PSO variants significantly. An application of the vehicle navigation optimization is also discussed in the paper, and the conducted experiment shows that the proposed approach to path navigation optimization saves travel time of real-time traffic navigation in a micro-scope traffic networks.

    Original languageEnglish
    Pages (from-to)351-364
    Number of pages14
    JournalTELECOMMUNICATION SYSTEMS
    Volume65
    Issue number3
    Early online date2016
    DOIs
    Publication statusPublished - 1 Jul 2017

    Keywords

    • Benchmark function
    • Monkey King Evolutionary algorithm
    • Number of function evaluation
    • Particle Swarm Optimization
    • Vehicle navigation
    • Wireless sensor network

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