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

Sanjoy Kumar Paul (), Ruhul Sarker and Daryl Essam
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Sanjoy Kumar Paul: RMIT University
Ruhul Sarker: The University of New South Wales
Daryl Essam: The University of New South Wales

Journal of Intelligent Manufacturing, 2018, vol. 29, issue 7, No 11, 1597 pages

Abstract: 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.

Keywords: Supply chain; Supply disruption; Reactive mitigation; Recovery plan; Mathematical model; Quantitative approach; Heuristic; Simulation (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s10845-016-1200-7

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