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ISPRS Int. J. Geo-Inf. 2018, 7(2), 77; https://doi.org/10.3390/ijgi7020077

Reliable Rescue Routing Optimization for Urban Emergency Logistics under Travel Time Uncertainty

1,2
,
3,4,* and 1,2
1
School of Geography Science and Planning, Center of Integrated Geographic Information Anlaysis, Sun Yat-sen University, Guangzhou 510275, China
2
Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China
3
Shenzhen Key Laboratory of Spatial Smart Sensing and Services & Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
4
Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and Geoinformation, Shenzhen University, Shenzhen 518060, China
*
Author to whom correspondence should be addressed.
Received: 20 December 2017 / Revised: 6 February 2018 / Accepted: 18 February 2018 / Published: 24 February 2018
(This article belongs to the Special Issue Human-Centric Data Science for Urban Studies)
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Abstract

The reliability of rescue routes is critical for urban emergency logistics during disasters. However, studies on reliable rescue routing under stochastic networks are still rare. This paper proposes a multiobjective rescue routing model for urban emergency logistics under travel time reliability. A hybrid metaheuristic integrating ant colony optimization (ACO) and tabu search (TS) was designed to solve the model. An experiment optimizing rescue routing plans under a real urban storm event, was carried out to validate the proposed model. The experimental results showed how our approach can improve rescue efficiency with high travel time reliability. View Full-Text
Keywords: urban emergency logistics; travel time reliability; rescue route optimization; a hybrid metaheuristic urban emergency logistics; travel time reliability; rescue route optimization; a hybrid metaheuristic
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Li, Q.; Tu, W.; Zhuo, L. Reliable Rescue Routing Optimization for Urban Emergency Logistics under Travel Time Uncertainty. ISPRS Int. J. Geo-Inf. 2018, 7, 77.

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