The purpose of this paper is to propose a model for allocating resources in various zones after a large-scale disaster. This study is motivated by the social dissatisfaction caused by inefficient relief distribution.
This study introduces an agent-based model (ABM) framework for integrating stakeholders’ interests. The proposed model uses the TOPSIS method to create a hierarchy of demand points for qualitative and quantitative parameters. A decomposition algorithm has been proposed to solve fleet allocation.
Relief distribution based on the urgency of demand points increases social benefit. A decomposition approach generates higher social benefit than the enumeration approach. The transportation cost is lower in the enumeration approach.
This study does not consider fleet contracts explicitly, but rather assumes a linear cost function for computing transportation costs.
The outcomes of this study can be a valuable tool for relief distribution planning. This model may also help reduce the social dissatisfaction caused by ad hoc relief distribution.
This study introduces an ABM for humanitarian logistics, proposes a decomposition approach, and explores the ontology of stakeholders of humanitarian logistics specific to last-mile distribution.
This work was supported by the Grant-in-Aid for Scientific Research C (24510184) awarded by the Japan Society for the Promotion of Science. Finally, the authors would like to thank the anonymous referees and the journal editorial board for their helpful comments and suggested improvements.
Das, R. and Hanaoka, S. (2014), "An agent-based model for resource allocation during relief distribution", Journal of Humanitarian Logistics and Supply Chain Management, Vol. 4 No. 2, pp. 265-285. https://doi.org/10.1108/JHLSCM-07-2013-0023Download as .RIS
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