Title: An intelligent hybridised distributed feedback control approach for the JIT open-shop scheduling problem

Authors: Azouz Meddourene; Brahim Bouzouia; Rosa Abbou; Nouara Achour

Addresses: Laboratory of Robotics, Parallelism and Electro-Magnetic (LRPE), University of Science and Technology (USTHB), Bab-Ezzouar, Algiers, Algeria; Manufacturing and Robotics Laboratory, Centre de Développement des Technologies Avancées (CDTA), Algiers, Algeria ' Manufacturing and Robotics Laboratory, Centre de Développement des Technologies Avancées (CDTA), Algiers, Algeria ' LS2N – UMR CNRS 6004, Université Bretagne Loire, Nantes, France ' Laboratory of Robotics, Parallelism and Electro-Magnetic (LRPE), University of Science and Technology (USTHB), Bab-Ezzouar, Algiers, Algeria

Abstract: In a real production environment, many companies are under pressure to increase customer satisfaction and reduce inventory costs. In this circumstance, production manufacturing within the just-in-time (JIT) approach should be combined with more flexibility. This paper proposes an intelligent hybrid approach called SA-DATC, which combines the two algorithms of simulated annealing (SA) and distributed arrival-time control (DATC) derived from control theory, to generate a reactive control strategy by combining the key advantages of each of them. The performances of the proposed method are tested on several randomly generated problems and are compared with quadratic linear program solutions to get a gauge of their relative effectiveness in a static environment. The results show the effectiveness of the proposed hybrid approach for JIT manufacturing by reducing production costs, production delays, and customer dissatisfaction.

Keywords: just-in-time; JIT; manufacturing control; open-shop scheduling; dynamic scheduling; arrival time control; simulated annealing.

DOI: 10.1504/IJSOM.2024.141412

International Journal of Services and Operations Management, 2024 Vol.49 No.1, pp.1 - 20

Received: 08 Jun 2022
Accepted: 11 Jun 2022
Published online: 12 Sep 2024 *

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