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An improved scatter search algorithm for solving job shop scheduling problems with parallel batch processing machine.

Hanpeng Wang1, Hengen Xiong2, Wenlu Zuo1

  • 1School of Mechanical Engineering, Wuhan University of Science and Technology, Wuhan, China.

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|April 8, 2025
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Summary
This summary is machine-generated.

This study introduces a new approach for automotive mold casting scheduling problems. An Improved Scatter Search algorithm optimizes job shop scheduling with parallel batch processing machines, minimizing completion times.

Keywords:
Batch job addition algorithmDecoding strategyImproved scatter searchJSP-PBPM

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Area of Science:

  • Operations Research
  • Manufacturing Systems Engineering
  • Computational Optimization

Background:

  • Automotive mold casting involves complex hybrid processing systems with single and parallel batch machines.
  • Existing job shop scheduling models often struggle with the complexities of parallel batch processing and precedence constraints.

Purpose of the Study:

  • To develop a novel job shop scheduling problem with parallel batch processing machines (JSP-PBPM) for automotive mold casting.
  • To minimize the maximum completion time in these hybrid manufacturing environments.

Main Methods:

  • A hybrid decoding strategy integrating batch job addition to handle operation precedence was developed.
  • An Improved Scatter Search (ISS) algorithm was designed, incorporating population initialization, solution improvement, reference set creation, subset generation, and solution refinement.

Main Results:

  • The proposed decoding strategy effectively addresses precedence constraints and enhances parallel batch machine utilization.
  • Simulation experiments demonstrated the feasibility and effectiveness of the ISS algorithm for solving the JSP-PBPM.

Conclusions:

  • The developed ISS algorithm and decoding strategy offer a robust solution for optimizing hybrid processing systems in automotive mold casting.
  • This research contributes to improved efficiency and reduced completion times in complex manufacturing scheduling.