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Memorias de investigación
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Double Ant Colony System to Improve Accessibility after a Disaster
Research Areas
  • Artificial intelligence,
  • Operative research
We propose a novel double ant colony system to deal with accessibility issues after a natural or man-made disaster. The aim is to maximize the number of survivors that reach the nearest regional center (center of economic and social activity in the region) in a minimum time by planning which rural roads damaged by the disaster should be repaired given the available financial and human resources. The double ant colony system considers pairs formed by an explorer and a worker ant. The aim of the explorer ant is to build paths from cities to their nearest regional centers, whereas the goal of the worker ant is to identify the optimal repair plan to maximize net accessibility. The two ants always work concurrently in pairs to build the paths and repair roads simultaneously. Candidate roads for repair have to be previously selected by the explorer ant in a transition rule, whereas the possibility of repairing a damaged road has to be taken into account when deciding which node to visit next. The proposed algorithm is illustrated by means of a large instance based on the Haiti natural disasters in August-September 2008, and its performance is compared with the combination of two metaheuristics: GRASP and VNS.
28th European Conference on Operational Research
Poznan, Polonia
Start Date
End Date
From page
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  • Autor: Víctor Sacristán
  • Autor: Antonio Jimenez Martin (UPM)
  • Autor: Alfonso Mateos Caballero (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de análisis de decisiones y estadística
  • Departamento: Inteligencia Artificial
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