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Open AccessArticle

A New Ant Colony-Based Methodology for Disaster Relief

1
Department of Financial and Actuarial Economics & Statistics, Interdisciplinary Mathematics Institute, Complutense University of Madrid, HUMLOG Research Group, 28040 Madrid, Spain
2
Department of Statistics and Operational Research, Interdisciplinary Mathematics Institute, Complutense University of Madrid, HUMLOG Research Group, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(4), 518; https://doi.org/10.3390/math8040518
Received: 2 March 2020 / Revised: 24 March 2020 / Accepted: 27 March 2020 / Published: 3 April 2020
(This article belongs to the Special Issue Optimization for Decision Making II)
Humanitarian logistics in response to large scale disasters entails decisions that must be taken urgently and under high uncertainty. In addition, the scarcity of available resources sometimes causes the involved organizations to suffer assaults while transporting the humanitarian aid. This paper addresses the last mile distribution problem that arises in such an insecure environment, in which vehicles are often forced to travel together forming convoys for security reasons. We develop an elaborated methodology based on Ant Colony Optimization that is applied to two case studies built from real disasters, namely the 2010 Haiti earthquake and the 2005 Niger famine. There are very few works in the literature dealing with problems in this context, and that is the research gap this paper tries to fill. Furthermore, the consideration of multiple criteria such as cost, time, equity, reliability, security or priority, is also an important contribution to the literature, in addition to the use of specialized ants and effective pheromones that are novel elements of the algorithm which could be exported to other similar problems. Computational results illustrate the efficiency of the new methodology, confirming it could be a good basis for a decision support tool for real operations. View Full-Text
Keywords: Ant Colony Optimization; humanitarian logistics; last mile distribution; disaster relief Ant Colony Optimization; humanitarian logistics; last mile distribution; disaster relief
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Ferrer, J.M.; Ortuño, M.T.; Tirado, G. A New Ant Colony-Based Methodology for Disaster Relief. Mathematics 2020, 8, 518.

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