A novel dynamic scheduling model for application in multimode approach

• Published in: Scientific reports Vol. 15; no. 1; pp. 27980 - 26
• Main Authors: Elqabli, Zineb, Kamach, Oulaid, Khatab, Abdelhakim, Chater, Youness
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 31.07.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/1041; 639/705/117; Artificial intelligence; Digital twins; Dynamic scheduling; Genetic algorithms; Humanities and Social Sciences; Job shops; Literature reviews; Makespan; Manufacturing; Methods; Modelling; multidisciplinary; Multimode approach; Optimization; Planning; Scheduling; Science; Science (multidisciplinary); Simulation; Value chain; Dynamic scheduling; Makespan; Modelling; Optimization; Multimode approach
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-025-10710-x

This study addresses job scheduling problem in multimode systems. A multimode system is designed to perform flexibly and reliably under normal and degraded modes in highly volatile environments. A novel job dynamic scheduling optimization model is proposed to enhance the multimode system resiliency and robustness to unexpected events. The formulated optimization problem is expressed as a MILP aimed at minimizing the makespan, subject to constraints reflecting the characteristics of multimode behavior. Quantitative data were gathered through requirement documents inspired from real-life scenarios. They comprise several elements related to processing times, jobs, operations, machines employed, and RUL prediction. Various experiments are conducted to demonstrate the validity and the accuracy of the proposed approach.