Publication

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
2010
Conference Papers

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.

Official source

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Evacuation Simulation with Limited Capacity Sinks - An Evolutionary Approach to Solve the Shelter Allocation and Capacity Assignment Problem in a Multi-agent Evacuation Simulation

Chat with Graph Search

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Design and experimental investigation of a herringbone grooved gas bearing supported turbocharger

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search