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An Improved African Vulture Optimization Algorithm for Dual-Resource Constrained Multi-Objective Flexible Job Shop

Zhou He1, Biao Tang2, Fei Luan2

  • 1School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi'an 710021, China.

Sensors (Basel, Switzerland)
|January 8, 2023
PubMed
Summary

This study introduces an improved African vulture optimization algorithm (IAVOA) to solve the dual-resource constrained flexible job shop scheduling problem (DRCFJSP), minimizing makespan and total delay effectively.

Keywords:
dual-resource constrained flexible job shop scheduling problemimproved African vulture algorithmmemory bankneighborhood search operationpopulation initialization

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Area of Science:

  • Operations Research
  • Industrial Engineering
  • Computational Intelligence

Background:

  • Flexible job shop scheduling problems (FJSP) are complex optimization challenges.
  • Dual-resource constraints (machines and workers) add significant complexity to FJSP.
  • Minimizing makespan and total delay are critical objectives in manufacturing.

Purpose of the Study:

  • To develop a novel optimization model for the dual-resource constrained flexible job shop scheduling problem (DRCFJSP).
  • To propose an improved African vulture optimization algorithm (IAVOA) for solving the DRCFJSP.
  • To minimize both the makespan and total delay in the scheduling process.

Main Methods:

  • Construction of a DRCFJSP model incorporating machine and worker constraints.
  • Development of a three-segment representation for operation sequence, machine allocation, and worker selection.
  • Enhancement of the African vulture optimization algorithm (AVOA) through improved population initialization, a memory bank, and a neighborhood search operation.

Main Results:

  • The proposed IAVOA demonstrates superior performance in solving the DRCFJSP compared to existing methods.
  • Simulation results validate the effectiveness of the IAVOA in optimizing makespan and total delay.
  • The enhancements to theAVOA significantly improve solution quality and calculation precision.

Conclusions:

  • The developed IAVOA is a highly effective approach for addressing the complexities of DRCFJSP.
  • The method provides a robust solution for minimizing makespan and total delay in flexible manufacturing environments.
  • This research contributes a valuable tool for optimizing scheduling in dual-resource constrained systems.