EVACUATION SIMULATION WITH LIMITED CAPACITY SINKS - An Evolutionary Approach to Solve the Shelter Allocation and Capacity Assignment Problem in a Multi-agent Evacuation Simulation

Gunnar Flötteröd, Gregor Lämmel

Abstract

We heuristically solve an evacuation problem with limited capacity shelters. An evolutionary learning algorithm is developed for the combined route- and shelter-assignment problem. It is complemented with a heuristic method for the fair minimization of shelter capacities. Different behavioral assumptions “fair” vs. “globally optimal”) are investigated. The proposed approaches are discussed in the context of a real-world tsunami evacuation problem.

References

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Paper Citation


in Harvard Style

Flötteröd G. and Lämmel G. (2010). EVACUATION SIMULATION WITH LIMITED CAPACITY SINKS - An Evolutionary Approach to Solve the Shelter Allocation and Capacity Assignment Problem in a Multi-agent Evacuation Simulation . In Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010) ISBN 978-989-8425-31-7, pages 249-254. DOI: 10.5220/0003086302490254


in Bibtex Style

@conference{icec10,
author={Gunnar Flötteröd and Gregor Lämmel},
title={EVACUATION SIMULATION WITH LIMITED CAPACITY SINKS - An Evolutionary Approach to Solve the Shelter Allocation and Capacity Assignment Problem in a Multi-agent Evacuation Simulation},
booktitle={Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)},
year={2010},
pages={249-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003086302490254},
isbn={978-989-8425-31-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)
TI - EVACUATION SIMULATION WITH LIMITED CAPACITY SINKS - An Evolutionary Approach to Solve the Shelter Allocation and Capacity Assignment Problem in a Multi-agent Evacuation Simulation
SN - 978-989-8425-31-7
AU - Flötteröd G.
AU - Lämmel G.
PY - 2010
SP - 249
EP - 254
DO - 10.5220/0003086302490254