Double Ant Colony System to Improve Accessibility after a Disaster

Víctor Sacristán, Antonio Jiménez-Martín, Alfonso Mateos


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 proposed algorithm is illustrated by means of a large instance based on the Haiti natural disasters in August-September 2008.


  1. Campbell, A., Lowe, T., and Zhang, L. (2006). Upgrading arcs to minimize the maximum travel time in a network. Networks, 477:72-80.
  2. Chen, H.-K., Chou, H.-W., Ho, P.-S., and Wang, H. (2011). Real-time vehicle routing for repairing damaged infrastructures due to natural disasters. Mathematical Problems in Engineering, 2011:25 pages.
  3. Chen, Y. and Tzeng, G. (1999). A fuzzy multiobjective model for reconstructing post-earthquake road-network by genetic algorithm. International Journal of Fuzzy Systems, 2:85-95.
  4. Cormen, T., Leiserson, C., and Rivest, R. (1990). Introduction to Algorithms. MIT Press, Cambridge.
  5. Donnges, C. (2003). Improving access in rural areas: Guidelines for integrated rural accessibility planning. Technical report, International Labour Organization.
  6. Dorigo, M. and Gambardela, L. (1997a). for the traveling salesman problem. 43(2):73-81.
  7. Dorigo, M. and Gambardela, L. (1997b). Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation, 1(1):53-66.
  8. Feng, C. and Wang, T. (2003). Highway emergency rehabilitation scheduling in post-earthquake 72 hours. Journal of the Eastern Asia Society for Transportation Studies, 5:3276-3285.
  9. Lebo, J. and Schelling, D. (2001). Design and appraisal of rural transport infrastructure ensuring basic access for rural communities. Technical report, World Bank.
  10. Lee, C. (2003). Using the genetic algorithm to solve the scheduling problem for repairing the post earthquake road networks. Master's thesis, National Cheng-Kung University, Taiwan.
  11. Liao, H. (2005). A study on network reconstruction and relief logistics. PhD thesis, National Central University, Taiwan.
  12. Maya, P. and S örensen, K. (2011). A grasp metaheuristic to improve accessibility after a disaster. OR Spectrum, 33:525-542.
  13. Moe, T. and Pathranarakul, P. (2006). An integrated approach to natural disaster management: Public project management and its critical success factors. Disaster Prevention Management, 15:396-413.
  14. Mu n˜oz, H., Jiménez-Martín, A., and Mateos, A. (2015). An ant colony system adaptation to deal with accessibility issues after a disaster. In Operations Research Proceedings 2014. Springer.
  15. OCHA-UN (2008). Haiti flash appeal 2008. Technical report, Office for the Coordination of Humanitarian Affairs.
  16. Sacristán, V. (2015). Análisis de la eficiencia de los sistemas de colonias de hormigas para problemas de accesibilidad. Master's thesis, Departamento de Inteligencia Artificial, Universidad Poli técnica de Madrid, Spain.
  17. Sato, T. and Ichii, K. (1996). Optimization of postearthquake restoration of lifeline networks using genetic algorithms. Japan Society of Civil Engineers, 53:245-256.
  18. Wang, F. (2008). Scheduling for repairing damaged networks under imprecise information in earthquakes. Master's thesis, Department of Civil Engineering, National Central University, Taiwan.
  19. Yan, S. and Shih, Y.-L. (2009). Optimal scheduling of emergency roadway repair and subsequent relief distribution. Computers and Operations Research, 36:2049- 2065.
  20. Yan, S. and Shih, Y.-L. (2012). An ant colony systembased hybrid algorithm for an emergency roadway repair time-space network flow problem. Transportmetrica, 8:361-386.
  21. Zhang, T. and Lu, Y. (2011). Study on simulation and optimization of the road rush-repair model after disaster. Applied Mechanic and Materials, 50:298-303.
  22. Zheng, Y.-J., Chen, S.-Y., and Ling, H.-F. (2015). Evolutionary optimization for disaster relief operations: A survey. Applied Soft Computing, 27:553-566.

Paper Citation

in Harvard Style

Sacristán V., Jiménez-Martín A. and Mateos A. (2016). Double Ant Colony System to Improve Accessibility after a Disaster . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 79-86. DOI: 10.5220/0005651900790086

in Bibtex Style

author={Víctor Sacristán and Antonio Jiménez-Martín and Alfonso Mateos},
title={Double Ant Colony System to Improve Accessibility after a Disaster},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},

in EndNote Style

JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Double Ant Colony System to Improve Accessibility after a Disaster
SN - 978-989-758-171-7
AU - Sacristán V.
AU - Jiménez-Martín A.
AU - Mateos A.
PY - 2016
SP - 79
EP - 86
DO - 10.5220/0005651900790086