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Gene Expression Programming with Multi-Threading Evaluation and Gene-Reuse Strategy

Published: 06 August 2020 Publication History

Abstract

As an approach widely used in automatic programming, the efficiency of the traditional GEP algorithm has gradually failed to meet the needs of users since its bottleneck in the evaluation phase. In this paper, a novel strategy named Gene-Reuse is proposed to improve the efficiency of GEP. In contrast to the traditional evaluation phase of GEP, the Gene-Reuse strategy features a novel mechanism that the Gene-Reuse strategy directly reads the pre-saved fitness value of chromosomes if these chromosomes have appeared in the previous population evolution. By applying that mechanism to the traditional GEP, the optimized algorithm can avoid many meaningless repeated calculations that improve the overall efficiency of the algorithm. Further, combining with multi-threading technology, a new Gene Expression Programming algorithm MTEGR-GEP that has significant performance compared with the traditional GEP algorithm is introduced to solve the existing problems of GEP mentioned above. Experimental results on several symbolic regression problems show that MTEGR-GEP has a significant improvement in efficiency compared to the traditional GEP.

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  1. Gene Expression Programming with Multi-Threading Evaluation and Gene-Reuse Strategy

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    HP3C 2020: Proceedings of the 2020 4th International Conference on High Performance Compilation, Computing and Communications
    June 2020
    191 pages
    ISBN:9781450376914
    DOI:10.1145/3407947
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University
    • City University of Hong Kong: City University of Hong Kong
    • Guangdong University of Technology: Guangdong University of Technology

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    New York, NY, United States

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    Published: 06 August 2020

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    Author Tags

    1. Gene Expression Programming (GEP)
    2. Gene-Reuse
    3. Multi-Threading Evaluation
    4. parallel computing

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