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Reliable Production Process Design Problem: Compact MILP Model and ALNS-Based Primal Heuristic

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Optimization and Applications (OPTIMA 2023)

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Abstract

Supply chain resilience is one of the most relevant topics of operations research and production management, which is aimed to risk mitigation in the global manufacturing, logistics, and trade. Conventional approach for resilient supply chain design involves the stochastic modeling and scenery-based description of anticipated failures in transportation networks. However, the stochastic approach can be insufficiently adequate in a situation of an unexpected failure or interruption. In this paper, we introduce the Reliable Production Process Design Problem (RPPDP), where the goal is to guarantee a suitable behaviour of the given highly distributed manufacturing system with respect to an (almost) arbitrary potential failure. This problem appears to be strongly NP-hard, similarly to the famous Constrained Shortest Path Tour and Shortest Simple Path with t Must Pass Nodes combinatorial problems. In order to find (close to) optimal solutions of the problem in question efficiently, we propose a compact Mixed Integer Linear Program (MILP) model and an Adaptive Large Neighborhood Search (ALNS) based primal heuristic. Results of their extensive numerical evaluation on top of the Gurobi branching framework, against the instances derived from the PCGTSPLIB library show high performance of the proposed methods.

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Acknowledgements

The work was performed as part of research carried out in the Ural Mathematical Center with the financial support of the Ministry of Science and Higher Education of the Russian Federation (Agreement number 075-02-2023-913).

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Authors and Affiliations

  1. Krasovsky Institute of Mathematics and Mechanics, Ekaterinburg, Russia

    Roman Rudakov, Yuri Ogorodnikov & Michael Khachay

  2. Kedge Business School, Bordeaux, France

    Daniil Khachai

Authors
  1. Roman Rudakov
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  2. Daniil Khachai
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  3. Yuri Ogorodnikov
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  4. Michael Khachay
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Corresponding author

Correspondence to Roman Rudakov .

Editor information

Editors and Affiliations

  1. FRC CSC RAS, Moscow, Russia

    Nicholas Olenev

  2. FRC CSC RAS, Moscow, Russia

    Yuri Evtushenko

  3. University of Montenegro, Podgorica, Montenegro

    Milojica Jaćimović

  4. Krasovsky Institute of Mathematics and Mechanics, Ekaterinburg, Russia

    Michael Khachay

  5. FRC CSC RAS, Moscow, Russia

    Vlasta Malkova

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Rudakov, R., Khachai, D., Ogorodnikov, Y., Khachay, M. (2023). Reliable Production Process Design Problem: Compact MILP Model and ALNS-Based Primal Heuristic. In: Olenev, N., Evtushenko, Y., Jaćimović, M., Khachay, M., Malkova, V. (eds) Optimization and Applications. OPTIMA 2023. Lecture Notes in Computer Science, vol 14395. Springer, Cham. https://doi.org/10.1007/978-3-031-47859-8_13

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  • DOI: https://doi.org/10.1007/978-3-031-47859-8_13

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  • Online ISBN: 978-3-031-47859-8

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