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An Enhanced Harmony Search Based on Quantum Mechanism

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Genetic and Evolutionary Computing (ICGEC 2021)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 833))

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Abstract

Harmony search (HS), which is widely used in many fields, is a meta-heuristic algorithm. In each iteration, HS generates a new solution under the harmony search consideration rate (HMCR) from harmony memory (HM). And the new solution is fine-tuned through a pitch adjustment rate (PAR). The basic HS obtains a random value from HM for each variable of a solution, and adjusts it in a fixed range. For the sake of improving its performance, we present an enhanced harmony search based on quantum mechanism (QEHS), which incorporates quantum concepts and differential mutation operation into the harmony search algorithm. QEHS reinforces the exploration and exploitation capability in search space, with the use of wave function from Schrödinger formula to express the harmony in HM. For reflecting the effectiveness of QEHS, simulations are carried on 30 benchmark functions from CEC2014. To manifest its feasibility, we compared the results of QEHS with that of other HS variants and some popular algorithms. Facts turn out that QEHS is an efficient and competitive algorithm.

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Acknowledgements

The writer is exceedingly grateful to all the reviewers and editors who spent their time and energy on this paper. This study is sustained by the Nature Science Foundation of Fujian Province of P. R. China (No. 2019J01401, No. 2021J01127), and the Special Fund for Scientific and Technological Innovation of Fujian Agriculture and Forestry University (No. CXZX2019117S, No. CXZX2020148C, No. CXZX2020150C), and Educational Research Project for Young and Middle-aged Teachers of Fujian Provincial Department of Education (JA170179), and in part by the Open Project Program of Digital Fujian Tourism Big Data Institute under Grant DFJTBDRI2020103.

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Authors and Affiliations

  1. College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China

    Maomao Liang, Ying Deng, Wen Xiao, Lijin Wang & Yiwen Zhong

  2. Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 350002, China

    Maomao Liang, Ying Deng, Wen Xiao, Lijin Wang & Yiwen Zhong

  3. Digital Fujian Tourism Big Data Institute (Wuyi University), Wuyishan, 354300, China

    Lijin Wang

Authors
  1. Maomao Liang
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  2. Ying Deng
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  3. Wen Xiao
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  4. Lijin Wang
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  5. Yiwen Zhong
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Corresponding author

Correspondence to Lijin Wang .

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Editors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China

    Shu-Chuan Chu

  2. Western Norway University of Applied Sciences, Bergen, Norway

    Jerry Chun-Wei Lin

  3. Northeast Electric Power University, Jilin City, Jilin, China

    Jianpo Li

  4. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China

    Jeng-Shyang Pan

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Liang, M., Deng, Y., Xiao, W., Wang, L., Zhong, Y. (2022). An Enhanced Harmony Search Based on Quantum Mechanism. In: Chu, SC., Lin, J.CW., Li, J., Pan, JS. (eds) Genetic and Evolutionary Computing. ICGEC 2021. Lecture Notes in Electrical Engineering, vol 833. Springer, Singapore. https://doi.org/10.1007/978-981-16-8430-2_5

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