Risk reduction for distribution of the perishable rescue items; A possibilistic programming approach

Shahparvari, S and Bodaghib, B 2018, 'Risk reduction for distribution of the perishable rescue items; A possibilistic programming approach', International Journal of Disaster Risk Reduction, vol. 31, pp. 886-901.


Document type: Journal Article
Collection: Journal Articles

Title Risk reduction for distribution of the perishable rescue items; A possibilistic programming approach
Author(s) Shahparvari, S
Bodaghib, B
Year 2018
Journal name International Journal of Disaster Risk Reduction
Volume number 31
Start page 886
End page 901
Total pages 16
Publisher Elsevier
Abstract The expedient transportation of relief supplies plays an undeniable role in minimizing human suffering and maximizing the survival rate in disaster-affected areas. Particularly during the 2009 Black Saturday bushfires in Australia, an investigation by the Victorian Bushfires Royal Commission revealed that resources such as medical teams and medical supplies were poorly coordinated during the initial response phase. Therefore, the aim of this study is to develop a mixed integer programming model to support tactical decision making in allocating emergency relief resources in the context of the Black Saturday bushfires. The proposed model uses historical data to determine the rescue vehicles' delivery loads and schedules based on vehicle capacity utilization, the supply of relief items and strict delivery time windows. Furthermore, a possibilistic programming approach has been employed to minimize the transportation disruption risk under uncertainty in the parameters and solve the model in a complex and unpredictable environment. To evaluate the reliability of the model, various sensitivity analyses have been applied while considering the priority level of the defined objectives. The results show that it would be possible to efficiently manage this emergency distribution context, even if one or two resources have very restricted delivery time constraints. However, disruption risk and priorities to the decision makers prove to impact resource utilization. The modeling outputs will be useful in the development of emergency plans and distribution coordination strategies to enhance rapid response to emergency relief distribution in disaster zones.
Subject Logistics and Supply Chain Management
Keyword(s) Disaster relief
Emergency operations
Optimization
Perishable items
Scheduling
Time windows
DOI - identifier 10.1016/j.ijdrr.2018.07.018
Copyright notice © 2018 Elsevier Ltd. All rights reserved.
ISSN 2212-4209
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