Performance Quantification of Search Operators in Hybrid Harmony Search Algorithms

Taewook Kim, Young Hwan Choi, Joong Hoon Kim

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Meta-heuristic algorithms have been developed to solve various mathematical and engineering optimization problems. However, meta-heuristic algorithms show different performances depending on the characteristics of each problem. Therefore, there have been many kinds of research to decrease the performance gap for the different optimization problems by developing new algorithms, improving the search operators, and considering self-adaptive parameters setting on their algorithms. However, the previous studies only focused on improving the performance of each problem category (e.g., mathematical problem, engineering problem) without the quantitative evaluation for the operator performance. Therefore, this study proposes a framework for the quantitative evaluation to solve the no free lunch problem using the operators of the representative meta-heuristic algorithms (such as genetic algorithm and harmony search algorithm). Moreover, based on the quantitative analysis results for each operator, there are several types of hybrid optimization algorithms, which combined the operator of harmony search algorithm (HSA), genetic algorithm (GA), and particle swarm optimization (PSO). The optimization process to find the optimal solution is divided into five sections based on the number of function evaluations to see the performance of the search operator according to the section. Representative mathematical problems were applied to quantify the performance and operators. None of the five evaluated applied to mathematical benchmark problems were the best algorithms. Hybrid HSAs showed advanced performance for problems where traditional HSA did not show good performance. However, it still has not escaped the No Free Lunch theorem.

    Original languageEnglish
    Title of host publicationProceedings of 6th International Conference on Harmony Search, Soft Computing and Applications - ICHSA 2020
    EditorsSinan Melih Nigdeli, Gebrail Bekdas, Joong Hoon Kim, Anupam Yadav
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages1-9
    Number of pages9
    ISBN (Print)9789811586026
    DOIs
    Publication statusPublished - 2021
    Event6th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2020 - Istanbul, Turkey
    Duration: 2020 Apr 222020 Apr 24

    Publication series

    NameAdvances in Intelligent Systems and Computing
    Volume1275
    ISSN (Print)2194-5357
    ISSN (Electronic)2194-5365

    Conference

    Conference6th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2020
    Country/TerritoryTurkey
    CityIstanbul
    Period20/4/2220/4/24

    Bibliographical note

    Funding Information:
    Acknowledgment This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No. 2019R1A2B5B03069810).

    Publisher Copyright:
    © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

    Keywords

    • Harmony search algorithm
    • Hybrid algorithm
    • Meta-heuristic algorithm
    • Operator
    • Performance quantification

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • General Computer Science

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