Ant Colony Optimization Model for Tsunamis Evacuation Routes

The results presented in this article showed that conventional evacuation routes in emergency situations showed longer escape times compared to those that are produced by the model developed in this research. Natural disasters such as earthquakes and tsunamis promoted the creation of effective evacuation strategies in order to prevent the loss of human lives. A simulation model was proposed in this article to discover optimum evacuation routes during a tsunami that used Ant Colony Optimization (ACO) algorithms. ACO were discrete optimization algorithms inspired by the ability of ants to establish the shortest path from their nest to a food source, and vice versa. Two drills were used to validate the model. These drills were conducted in the coastal town of Penco, Chile, a town that was affected by an 8.8 Mw earthquake and tsunami in February 2010. The first drill was held with minimal information, leaving the population to act randomly and intuitively and the second drill was carried out with information provided by the model, inducing people to use the optimized routes generated by the ACO algorithm.

[1]  Qingfeng Sun,et al.  Research on transportation route optimization among emergency evacuation , 2011, 2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC).

[2]  S. Travis Waller,et al.  A Hybrid Bilevel Model for the Optimal Shelter Assignment in Emergency Evacuations , 2010, Comput. Aided Civ. Infrastructure Eng..

[3]  Monique Snoeck,et al.  Classification With Ant Colony Optimization , 2007, IEEE Transactions on Evolutionary Computation.

[4]  Shengwu Xiong,et al.  Multi-objective ant colony optimization model for emergency evacuation , 2010, 2010 Sixth International Conference on Natural Computation.

[5]  Miroslaw J. Skibniewski,et al.  Multiheuristic Approach for Resource Leveling Problem in Construction Engineering: Hybrid Approach , 1999 .

[6]  Tao Yao,et al.  Evacuation Transportation Planning Under Uncertainty: A Robust Optimization Approach , 2009 .

[7]  Yong Qin,et al.  Research the strategy of the highway transportation in the earthquake , 2008, 2008 IEEE International Conference on Service Operations and Logistics, and Informatics.

[8]  Alex A. Freitas,et al.  An Ant Colony Algorithm for Classification Rule Discovery , 2002 .

[9]  Tarek Hegazy,et al.  MOST‐FIT: Support Techniques for Inspection and Life Cycle Optimization in Building Asset Management , 2012, Comput. Aided Civ. Infrastructure Eng..

[10]  Hong Zheng,et al.  Modeling no-notice mass evacuation using a dynamic traffic flow optimization model , 2007 .

[11]  R. Madariaga,et al.  Central Chile Finally Breaks , 2010, Science.

[12]  Wei-Yen Hsu.  Application of Quantum-behaved Particle Swarm Optimization to Motor imagery EEG Classification , 2013, Int. J. Neural Syst..

[13]  Karim C. Abbaspour,et al.  Estimating unsaturated soil hydraulic parameters using ant colony optimization , 2001 .

[14]  Said Kerrache,et al.  An Optimal Transport-Based Approach for Crowd Evacuation , 2013, 2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation.

[15]  Léon J. M. Rothkrantz,et al.  Ant-Based Load Balancing in Telecommunications Networks , 1996, Adapt. Behav..

[16]  Chih-Yuan Chu,et al.  A Computer Model for Selecting Facility Evacuation Design Using Cellular Automata , 2009, Comput. Aided Civ. Infrastructure Eng..

[17]  Hong Jiang,et al.  An improved Ant Colony algorithm for Urban Transit Network Optimization , 2010, 2010 Sixth International Conference on Natural Computation.

[18]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[19]  Jing Wang,et al.  A wavelet-based particle swarm optimization algorithm for digital image watermarking , 2012, Integr. Comput. Aided Eng..

[20]  Baher Abdulhai,et al.  Large-Scale Evacuation Using Subway and Bus Transit: Approach and Application in City of Toronto , 2012 .

[21]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[22]  Pengfei Duan,et al.  Multi-objective optimization model based on heuristic ant colony algorithm for emergency evacuation , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[23]  Hojjat Adeli,et al.  Life‐cycle cost optimization of steel structures , 2002 .

[24]  A. Kaveh,et al.  Optimal Design of Scissor-Link Foldable Structures Using Ant Colony Optimization Algorithm , 2007, Comput. Aided Civ. Infrastructure Eng..

[25]  Manolis Papadrakakis,et al.  A Hybrid Particle Swarm—Gradient Algorithm for Global Structural Optimization , 2010, Comput. Aided Civ. Infrastructure Eng..

[26]  Ivan Damnjanovic,et al.  Agent‐Based Modeling of Behavioral Housing Recovery Following Disasters , 2012, Comput. Aided Civ. Infrastructure Eng..

[27]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[28]  Suzanne Wilkinson,et al.  Build Back Better principles for post‐disaster structural improvements , 2013 .

[29]  Luca Quadrifoglio,et al.  Comparing Ant Colony Optimization and Genetic Algorithm Approaches for Solving Traffic Signal Coordination under Oversaturation Conditions , 2012, Comput. Aided Civ. Infrastructure Eng..