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Predictive-reactive Strategy for Flowshop Rescheduling Problem: Minimizing the Total Weighted Waiting Times and Instability

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Abstract

Due to the fourth revolution experiencing, referred to as Industry 4.0, many production firms are devoted to integrating new technological tools to their manufacturing process. One of them, is rescheduling the tasks on the machines responding to disruptions. While, for static scheduling, the efficiency criteria measure the performance of scheduling systems, in dynamic environments, the stability criteria are also used to assess the impact of jobs deviation. In this paper, a new performance measure is investigated for a flowshop rescheduling problem. This one considers simultaneously the total weighted waiting time as the efficiency criterion, and the total weighted completion time deviation as the stability criterion. This fusion could be a very helpful and significant measure for real life industrial systems. Two disruption types are considered: jobs arrival and jobs cancellation. Thus, a Mixed Integer Linear Programming (MILP) model is developed, as well as an iterative predictive-reactive strategy for dealing with the online part. At last, two heuristic methods are proposed and discussed, in terms of solution quality and computing time.

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Acknowledgments

The authors greatly appreciate the comments of the editor and the referees, which were very helpful for improving the quality of the paper. This work is financially supported by Communauté d’Agglomération Sarreguemines Confluences, France and Région Grand Est, France.

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Authors and Affiliations

  1. Université de Lorraine, LGIPM, F-57000, Metz, France

    Ayoub Tighazoui, Christophe Sauvey & Nathalie Sauer

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  1. Ayoub Tighazoui
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  2. Christophe Sauvey
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  3. Nathalie Sauer
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Correspondence to Ayoub Tighazoui.

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Ayoub Tighazoui is a Ph.D. student at the LGIPM (Laboratory of Informatics Engineering, Production and Maintenance) of the “Université de Lorraine” in Metz, France, from which he received his Master’s degree in industrial systems engineering in 2018. He also received his engineer degree in industrial engineering in 2014 from ENSA (National School of Applied Sciences) in Safi, Morocco. His areas of expertise include: mathematical modelling, optimisation methods, operations research, scheduling and applications.

Christophe Sauvey is an assistant professor at the LGIPM (Laboratory of Informatics Engineering, Production and Maintenance) of the “Université de Lorraine”, in Metz, France. He received his engineer degree in electrical engineering from the Polytechnic National Institute of Grenoble (France) in 1997 and his PhD in 2000, on the modelling and optimisation of switched reluctance motors. He received his accreditation to supervise research on modelling and optimisation methods in 2021. His areas of expertise include mathematical modelling, optimisation methods, supply chain management, healthcare systems, logistics, scheduling and applications.

Nathalie Sauer is full professor at the “Université de Lorraine”, Metz, France. She received the M.S. degree in applied mathematics, University of Paris 6, in 1991, the PhD degree in industrial engineering from the University of Metz, France, in 1994, and the HDR (accreditation to supervise research) from the University of Nantes, France, in 2004. In 2005, she joined LGIPM (Laboratory of Informatics Engineering, Production and Maintenance), Metz, and she is currently deputy director of this laboratory. Her research interests include scheduling problems, operations research, modeling, analysis and logistic and production systems optimization.

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Tighazoui, A., Sauvey, C. & Sauer, N. Predictive-reactive Strategy for Flowshop Rescheduling Problem: Minimizing the Total Weighted Waiting Times and Instability. J. Syst. Sci. Syst. Eng. 30, 253–275 (2021). https://doi.org/10.1007/s11518-021-5490-8

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