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A novel dynamic scheduling model for application in multimode approach.

Zineb Elqabli1, Oulaid Kamach2, Abdelhakim Khatab3

  • 1Innovative Technologies Laboratory, National School of Applied Sciences Tangier, Tangier, Morocco. Zineb.elqabli@etu.uae.ac.ma.

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Summary
This summary is machine-generated.

This study introduces a job scheduling optimization model for multimode systems, enhancing their resilience. The model minimizes system downtime in volatile environments by dynamically adjusting job schedules.

Keywords:
Dynamic schedulingMakespanModellingMultimode approachOptimization

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Area of Science:

  • Operations Research
  • Industrial Engineering
  • System Resilience Engineering

Background:

  • Multimode systems are designed for flexibility and reliability in dynamic environments, operating under normal and degraded conditions.
  • Job scheduling in these systems faces challenges due to volatility and unexpected events, impacting overall system performance and robustness.

Purpose of the Study:

  • To propose a novel job dynamic scheduling optimization model for multimode systems.
  • To enhance the resiliency and robustness of multimode systems against unexpected disruptions.
  • To minimize the makespan in job scheduling for multimode systems.

Main Methods:

  • Formulation of a Mixed-Integer Linear Programming (MILP) optimization problem.
  • Inclusion of constraints that capture the specific behaviors and characteristics of multimode systems.
  • Utilization of quantitative data from real-life scenarios, including processing times, job details, operations, machine assignments, and Remaining Useful Life (RUL) predictions.

Main Results:

  • Demonstration of the proposed model's validity through various experiments.
  • Validation of the model's accuracy in optimizing job schedules for multimode systems.
  • Evidence of enhanced system resiliency and robustness under simulated volatile conditions.

Conclusions:

  • The proposed MILP model effectively optimizes job scheduling in multimode systems.
  • The dynamic scheduling approach improves system robustness against unexpected events.
  • The study provides a validated method for enhancing multimode system performance in challenging environments.