Design of level of service on facilities for crowd evacuation using genetic algorithm optimization

Li, Y.; Cai, Wei; Kana, A.A.

doi:10.1016/j.ssci.2019.06.044

Design of level of service on facilities for crowd evacuation using genetic algorithm optimization

Title

Design of level of service on facilities for crowd evacuation using genetic algorithm optimization

Author

Li, Y. (TU Delft Ship Design, Production and Operations; Wuhan University of Technology)
Cai, Wei (Wuhan University of Technology)
Kana, A.A. (TU Delft Ship Design, Production and Operations)

Date

2019

Abstract

This paper introduces a novel technique to design the level of service (LOS) for facilities or sub spaces of buildings for the purpose of evacuation planning. LOS is a standard qualitative indicator used to describe flow characteristics in a pedestrian environment. Some evacuation planners use LOS to help determine the network parameters when solving evacuation planning problems by the network flow approach. However, there is currently limited research into the optimization of the LOS parameters themselves to construct more efficient evacuation networks. In this paper the authors used a genetic algorithm optimization approach to determine LOS for facilities to improve the evacuation performance of building networks. Each individual chromosome containing a LOS design represents a fully defined evacuation network that can be solved. The fitness of each network is measured by minimum clearance time, which is calculated by the Capacity Constrained Route Planner (CCRP) approach. A comparative computational test in a hypothetical three-story building shows that the evacuation network under the optimized LOS design has a roughly 11% less minimum clearance time compared to the network under the original LOS design. Sensitivity analysis is also included, focusing on how the population size and the building layout influence the LOS design. In addition, an additional computational test for a twelve-deck cruise ship shows that the approach is scalable to solve more complex evacuation networks. The proposed approach has the potential to provide better LOS assignments for facilities for the government officials to develop effective emergency management strategies.

Subject

Evacuation planning
Genetic algorithm
Level of service
Network flow model
Network parameters

To reference this document use:

http://resolver.tudelft.nl/uuid:e9e5bb7c-947c-4a5e-95d4-9273d9f72775

DOI

https://doi.org/10.1016/j.ssci.2019.06.044

Embargo date

2022-07-10

ISSN

0925-7535

Source

Safety Science, 120, 237-247