Scholarlink

<p>The existing researches about flexible job shop scheduling problem (FJSP) commonly assumes that the quality of all completed operations is qualified, and ignores the quality abnormality caused by machine fault. However, in the real manufacturing process, the processing quality of the process is uncertain, and the operation inspection is a crucial way to reduce the flow of abnormal jobs to the next manufacturing units or customers. Additionally, some machine faults can be determined and repaired in time through the results of operation inspection to avoid further production of abnormal products. Hence, we formulate a mathematical model for the dynamic FJSP with quality abnormality caused by machine fault (FJSPM), aiming at minimizing the makespan, maximum workload of the machines and total energy consumption. An improved two-stage memetic algorithm (ITMA) is developed to solve the proposed FJSPM. In the first phase, a variable heuristic initialization method (VHI) including three heuristic rules is designed to obtain superior initial populations. A multi-neighborhood search operator (MSO) comprising four neighborhood structures is devised to accelerate its convergence. In the second phase, a well-designed interval insertion rescheduling method (IRS) considering two strategies is utilized to address the different inspection results. Extensive experiments based on 60 constructed FJSPM benchmark instances verify the effectiveness of the MSO and IRS, and demonstrate the superior performance of ITMA in solving the FJSPM by comparing it with the other four comparison algorithms.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Dynamic scheduling for flexible job-shop with quality abnormality caused by machine fault

  • 期刊论文

  • 发表日期：

    2025年9月3日

查看全文
  • Kaikai Zhu,
  • Guiliang Gong,
  • Xiaobin Li,
  • Ningtao Peng,
  • Jiuqiang Tang

摘要

The existing researches about flexible job shop scheduling problem (FJSP) commonly assumes that the quality of all completed operations is qualified, and ignores the quality abnormality caused by machine fault. However, in the real manufacturing process, the processing quality of the process is uncertain, and the operation inspection is a crucial way to reduce the flow of abnormal jobs to the next manufacturing units or customers. Additionally, some machine faults can be determined and repaired in time through the results of operation inspection to avoid further production of abnormal products. Hence, we formulate a mathematical model for the dynamic FJSP with quality abnormality caused by machine fault (FJSPM), aiming at minimizing the makespan, maximum workload of the machines and total energy consumption. An improved two-stage memetic algorithm (ITMA) is developed to solve the proposed FJSPM. In the first phase, a variable heuristic initialization method (VHI) including three heuristic rules is designed to obtain superior initial populations. A multi-neighborhood search operator (MSO) comprising four neighborhood structures is devised to accelerate its convergence. In the second phase, a well-designed interval insertion rescheduling method (IRS) considering two strategies is utilized to address the different inspection results. Extensive experiments based on 60 constructed FJSPM benchmark instances verify the effectiveness of the MSO and IRS, and demonstrate the superior performance of ITMA in solving the FJSPM by comparing it with the other four comparison algorithms.