Optimization Spiking Neural P System for Solving TSP

Feng Qi; Mengmeng Liu

Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part II

Research Article

Optimization Spiking Neural P System for Solving TSP

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@INPROCEEDINGS{10.1007/978-3-319-73447-7_71,
    author={Feng Qi and Mengmeng Liu},
    title={Optimization Spiking Neural P System for Solving TSP},
    proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part II},
    proceedings_a={MLICOM},
    year={2018},
    month={2},
    keywords={OSNPS GA Membrane algorithm TSP},
    doi={10.1007/978-3-319-73447-7_71}
}

Feng Qi
Mengmeng Liu
Year: 2018
Optimization Spiking Neural P System for Solving TSP
MLICOM
Springer
DOI: 10.1007/978-3-319-73447-7_71

Feng Qi¹^,*, Mengmeng Liu¹^,*

1: Shandong Normal University

*Contact email: qfsdnu@126.com, 1783797657@qq.com

Abstract

Spiking neural P systems are a class of distributed and parallel computing models that incorporate the idea of spiking neurons into P systems. Membrane computing (MC) combining with evolutionary computing (EC) is called evolutionary MC. In this work, we will combine SNPS with heuristic algorithm to solve the travelling salesman problem. To this aim, an extended spiking neural P system (ESNPS) has been proposed. A certain number of ESNPS can be organized into OSNPS. Extensive experiments on TSP have been reported to experimentally prove the viability and effectiveness of the proposed neural system.

Keywords: OSNPS GA Membrane algorithm TSP

Published: 2018-02-09
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-319-73447-7_71