TY - GEN
T1 - Bus Routing for emergency evacuations
T2 - 2017 IEEE Congress on Evolutionary Computation, CEC 2017
AU - Vitali, Javiera Loyola
AU - Riff, Maria Cristina
AU - Montero, Elizabeth
N1 - Funding Information:
† Supported by FONDECYT Project no. 1151456. Partially supported by the Centro Científico Tecnológico de Valparaíso (CCTVal) no. FB0821 ‡ Supported by FONDECYT Initiation into Research Project no. 11150787
PY - 2017/7/5
Y1 - 2017/7/5
N2 - The Bus Evacuation Problem is a route planning problem, in the context of an evacuation in an emergency situation. Considering that public transport is available to support the evacuation, the objective of the problem is to determine the best route for each vehicle, to move all the people from a risk zone to open shelters located in safe zones, such that the evacuation time is minimized. In this work we present a method based on the Greedy Randomized Adaptive Search Procedure metaheuristic to solve the problem, in order to apply the solution to a real-world scenario based on a recent wildfire on Valparaíso, Chile. In computational experiments we demonstrate that our approach is effective to solve real-world size problems, and able to outperform a commercial MIP solver.
AB - The Bus Evacuation Problem is a route planning problem, in the context of an evacuation in an emergency situation. Considering that public transport is available to support the evacuation, the objective of the problem is to determine the best route for each vehicle, to move all the people from a risk zone to open shelters located in safe zones, such that the evacuation time is minimized. In this work we present a method based on the Greedy Randomized Adaptive Search Procedure metaheuristic to solve the problem, in order to apply the solution to a real-world scenario based on a recent wildfire on Valparaíso, Chile. In computational experiments we demonstrate that our approach is effective to solve real-world size problems, and able to outperform a commercial MIP solver.
UR - http://www.scopus.com/inward/record.url?scp=85027838683&partnerID=8YFLogxK
U2 - 10.1109/CEC.2017.7969589
DO - 10.1109/CEC.2017.7969589
M3 - Conference contribution
AN - SCOPUS:85027838683
T3 - 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
SP - 2346
EP - 2353
BT - 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 June 2017 through 8 June 2017
ER -