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A reactive mitigation approach for managing supply disruption in a three-tier supply chain

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Abstract

In this paper, we develop a quantitative reactive mitigation approach for managing supply disruption for a supply chain. We consider a three-tier supply chain system with multiple raw material suppliers, a single manufacturer and multiple retailers, where the system may face sudden disruption in its raw material supply. First, we develop a mathematical model that generates a recovery plan after the occurrence of a single disruption. Here, the objective is to minimize the total cost during the recovery time window while being subject to supply, capacity, demand, and delivery constraints. We develop an efficient heuristic to solve the model for a single disruption. Second, we also consider multiple disruptions, where a new disruption may or may not affect the recovery plans of earlier disruptions. We also develop a new dynamic mathematical and heuristic approach that is capable of dealing with multiple disruptions, after the occurrence of each disruption as a series, on a real-time basis. We compare the heuristic solutions with those obtained by a standard search algorithm for a set of randomly generated disruption test problems, which shows the consistent performance of our heuristic. Finally, a simulation model is developed to analyze the effect of randomly generated disruption events that are not known in advance. The numerical results and many random experiments are presented to explain the usefulness of the developed models and methodologies.

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Author information

Authors and Affiliations

  1. School of Business IT and Logistics, RMIT University, Melbourne, Australia

    Sanjoy Kumar Paul

  2. School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia

    Ruhul Sarker & Daryl Essam

Authors
  1. Sanjoy Kumar Paul
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  2. Ruhul Sarker
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  3. Daryl Essam
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Corresponding author

Correspondence to Sanjoy Kumar Paul.

Appendices

Appendix 1

Parameters of PS technique

In the proposed PS based solution approach, following PS parameters are used to solve the model.

  • Maximum number of iterations: 100* Number of variables

  • Polling order: Random

  • X tolerance: 1e-8

  • Function tolerance: 1e-8

  • Non-linear constraint tolerance: 1e-8

  • Cache tolerance: 1e-8

  • Search method: Latin hypercube

  • Maximum function evaluations: \(10^{6}\)

Other parameters are set as the default in the optimization toolbox of MATLAB R2012a.

Appendix 2

See Table 6.

Table 6 Revised plans for disruption instances 1 and 2
Full size table

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Paul, S.K., Sarker, R. & Essam, D. A reactive mitigation approach for managing supply disruption in a three-tier supply chain. J Intell Manuf 29, 1581–1597 (2018). https://doi.org/10.1007/s10845-016-1200-7

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