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A simheuristic approach using the NSGA-II to solve a bi-objective stochastic flexible job shop problem

Author

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  • Camilo Andrés Rodríguez-Espinosa
  • Eliana María González-Neira
  • Gabriel Mauricio Zambrano-Rey

Abstract

This paper addresses a bi-objective problem in flexible job shop scheduling (FJSS) with stochastic processing times. Following the Just-In-Time philosophy, the first objective is to minimise deterministic Earliness+Tardiness, and the second objective is to minimise the Earliness+Tardiness Risk. The second objective function seeks to obtain robust solutions under uncertain environments. The proposed approach is a simheuristic that hybridises the non-dominated sorting genetic algorithm (NSGA-II) with Monte Carlo simulation to obtain the Pareto frontier of both objectives. The computational results demonstrate the effectiveness of the proposed algorithm under different variability environments.

Suggested Citation

  • Camilo Andrés Rodríguez-Espinosa & Eliana María González-Neira & Gabriel Mauricio Zambrano-Rey, 2024. "A simheuristic approach using the NSGA-II to solve a bi-objective stochastic flexible job shop problem," Journal of Simulation, Taylor & Francis Journals, vol. 18(4), pages 646-670, July.
    • Handle: RePEc:taf:tjsmxx:v:18:y:2024:i:4:p:646-670
    DOI: 10.1080/17477778.2023.2231877
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