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Mixed-Integer Programming and Constraint Programming Models for the Flexible Job Shop Scheduling Problem

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Artificial Intelligence and Industrial Applications (A2IA 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 771))

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Abstract

The flexible job-shop scheduling problem (FJSP) is considered as an important problem in the modern manufacturing system. It is one of the most difficult problems in this area. In fact, this problem is a generalized and more complicated variant of the classical job-shop that introduces an additional decision level known as the assignment sub-problem in addition to the sequencing sub-problem. In this paper, we study the flexible job-shop scheduling problem under partial and total flexibility. The objective aims to minimize the total completion time. Nothing that mainly metaheuristic approaches have been considered for solving FJSP and only limited research actually makes use of their mathematical models to design exact approaches. We therefore propose two mathematical models, a mixed-integer linear programming model (MILP) and a constraint programming model (CP). Test experiments are performed on a large set of randomly generated instances using CPLEX software. The acquired results show the efficiency of the developed models for solving both partially and totally FJSP problems. Experimental results prove also the competitiveness of the CP model, compared to the MILP model, in solving large size FJSP problem with a reasonable processing time.

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Author information

Authors and Affiliations

  1. LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, 1002, Tunis, Tunisia

    Asma Fekih, Hatem Hadda & Atidel B. Hadj-Alouane

  2. Université de Lorraine. Laboratoire LCOMS EA, 7306, Metz, France

    Imed Kacem

  3. Industrial Engineering and Engineering Management Department, College of Engineering, University of Sharjah, Box 27272, Sharjah, United Arab Emirates

    Atidel B. Hadj-Alouane

Authors
  1. Asma Fekih
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  2. Hatem Hadda
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  3. Imed Kacem
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  4. Atidel B. Hadj-Alouane
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Corresponding author

Correspondence to Asma Fekih .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, National Graduate School for Arts and Crafts, Meknes, Morocco

    Tawfik Masrour

  2. Department of Industrial and Manufacturing Engineering, National Graduate School for Arts and Crafts, Meknes, Morocco

    Ibtissam El Hassani

  3. Department of Mathematics, Computer Science and Engineering at UQAR University, Rimouski, QC, Canada

    Noureddine Barka

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Fekih, A., Hadda, H., Kacem, I., Hadj-Alouane, A.B. (2023). Mixed-Integer Programming and Constraint Programming Models for the Flexible Job Shop Scheduling Problem. In: Masrour, T., El Hassani, I., Barka, N. (eds) Artificial Intelligence and Industrial Applications. A2IA 2023. Lecture Notes in Networks and Systems, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-031-43524-9_8

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