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An QUasi-Affine TRansformation Evolution (QUATRE) Algorithm for Job-Shop Scheduling Problem by Mixing Different Strategies

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Advances in Smart Vehicular Technology, Transportation, Communication and Applications

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 250))

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Abstract

How to solve the Job-Shop Scheduling problem (JSP) effectively and make the most efficient use of resources has always been the focus of academic and engineering circles. Aiming at the traditional JSP problem, this paper proposes a new QUasi-Affine Transformation Evolution algorithm (QUATRE) to solve it, called QUATRE-SAO for short. The QUATRE-SAO algorithm combines Simulated Annealing (SA) strategy and Opposition-based Learning (OBL) strategy to enhance the algorithm to jump out of local optimum and further improve the optimization performance of the algorithm. Through the comparative experiment of FT and LA series standard test examples, the results show that the QUATRE-SAO algorithm can solve the JSP problem better and can get a better solution.

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Author information

Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Qing-Yong Yang, Shu-Chuan Chu, Chien-Ming Chen & Jeng-Shyang Pan

Authors
  1. Qing-Yong Yang
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  2. Shu-Chuan Chu
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  3. Chien-Ming Chen
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  4. Jeng-Shyang Pan
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Editor information

Editors and Affiliations

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

    Tsu-Yang Wu

  2. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan, China

    Shaoquan Ni

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

    Shu-Chuan Chu

  4. College of Computer and Data Science, Fuzhou University, Fuzhou, China

    Chi-Hua Chen

  5. Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita Favorskaya

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Yang, QY., Chu, SC., Chen, CM., Pan, JS. (2022). An QUasi-Affine TRansformation Evolution (QUATRE) Algorithm for Job-Shop Scheduling Problem by Mixing Different Strategies. In: Wu, TY., Ni, S., Chu, SC., Chen, CH., Favorskaya, M. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. Smart Innovation, Systems and Technologies, vol 250. Springer, Singapore. https://doi.org/10.1007/978-981-16-4039-1_16

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  • DOI: https://doi.org/10.1007/978-981-16-4039-1_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-4038-4

  • Online ISBN: 978-981-16-4039-1

  • eBook Packages: EngineeringEngineering (R0)

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