Abstract

A supply chain disruption is an unanticipated event that disrupts the flow of materials in a supply chain. Any given supply chain disruption could have a significant negative impact on the entire supply chain. Supply chain network designs usually consider two stage of decision process in a business environment. The first stage deals with strategic levels, such as to determine facility locations and their capacity, while the second stage considers in a tactical level, such as production quantity, delivery routing. Each stage’s decision could affect the other stage’s result, and it could not be determined individual. However, supply chain network designs often fail to account for supply chain disruptions. In this paper, this paper proposed a two-stage stochastic programming model for a four-echelon global supply chain network design problem considering possible disruptions at facilities. A modified simulated annealing (SA) algorithm is developed to determine the strategic decision at the first stage. The comparison of traditional supply chain network decision framework shows that under disruption, the stochastic solutions outperform the traditional one. This study demonstrates the managerial viability of the proposed model in designing a supply chain network in which disruptive events are proactively accounted for.

Highlights

  • Chain network design constitutes a crucial decision-making process that affects organizational performance, especially given the highly volatile nature of a business environment characterized by various sources of risk and uncertainty

  • In order to test the effectiveness of the proposed method, the results are compared from the heuristic to the optimal objective value obtained from CPLEX by solving a small sampled version of the model with sample size N = 10

  • The same sampled problem is solved for 10 replications for the heuristic

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Summary

Introduction

Chain network design constitutes a crucial decision-making process that affects organizational performance, especially given the highly volatile nature of a business environment characterized by various sources of risk and uncertainty. The massive floods that took place in Thailand in 2011 offer a case study of global supply chain disruption, especially in the electronic and automotive industries. Western Digital, Sony, and Honda were all obliged to stop production due to the direct flooding of their factories, while Toyota suffered from an indirect impact due to the disruption experienced by key suppliers [1] A proactive supply chain network design decision framework is, vital for all enterprises [2,3,4]. A two-stage stochastic programming model in which the possibility of a facility disruption is accounted for is formulated to solve a supply chain network design problem. Compared to other methods such as deterministic model or Mixed Integer

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