A Continuous Approximation Approach Based on Regular Hexagon Partition for the Facility Location Problem under Disruptions Risk

Today’s business environment is complex, dynamic, and uncertain which makes a supply chain facility increasingly vulnerable to disruption from various risk accidents as one of the main threats to the whole supply chain’s operation. However, in general, most of the studies on facility location proble...

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Bibliographic Details
Published inComplexity (New York, N.Y.) Vol. 2019; no. 2019; pp. 1 - 12
Main Authors Wang, Jiguang, Wu, Yucai
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 01.01.2019
Hindawi
John Wiley & Sons, Inc
Wiley
Subjects
Accidents
Approximation
Construction costs
Decision making
Disruption
Management science
Mathematical analysis
Operations management
Operations research
Partitions
Plant location
Reliability
Risk
Site selection
Statistical analysis
Suppliers
Supply chains
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Summary:Today’s business environment is complex, dynamic, and uncertain which makes a supply chain facility increasingly vulnerable to disruption from various risk accidents as one of the main threats to the whole supply chain’s operation. However, in general, most of the studies on facility location problems assume that the facilities, once built, will always run availably and reliably. In fact, although the probability is very low, supply chain disruptions often incur disastrous consequences. Therefore, it is critical to account for disruptions during designing supply chain networks. To accomplish planned outcomes and greater supply chain resiliency, this article proposes a continuous approximation approach based on regular hexagon partition to address the reliable facility location problems with consideration of facility disruptions risk. The optimization goal is to determine the best facility location that minimizes the expected total system cost on the premise that the supply chain network is not disrupted as a whole when one or some facilities are subject to probabilistic failure. Our numerical experiment discusses the performance of the proposed solution approaches which demonstrates that the benefits of considering disruptions in the supply chain design can be significant. In addition, considering the impact of disruption probability estimation error on the optimal decision, the misestimating of the disruption probability is also investigated in this paper.
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ISSN:1076-2787
1099-0526
DOI:10.1155/2019/5280161