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Snow removal resource location and allocation optimization for urban road network recovery: a resilience perspective

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Abstract

Recently, the vulnerability of urban road network has become increasingly obvious in the face of natural emergencies. The extreme snow weather, a kind of natural emergencies, can severely reduce the service capability of road network. It has attracted a wide attention that how the urban road network system get recovered after such unexpected events. In this paper, we proposed the urban road network resilience evacuation method under snow event. In order to improve the resilience of road network, we establish the mathematical model for road network recovery under extreme weather to solve the snow removal resource location-allocation problem (LAP) with uncertain weather information. The routes for snow removal vehicle are determined as several Vehicle Routing Problems (VRPs). The corresponding tabu search algorithm is designed. Finally, we verify the effectiveness of proposed model and algorithm by a real case to provide decision-making support for the city traffic management departments and enhance the resilience of city in the extreme snow weather.

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Acknowledgements

This Project has received funding from National Social Science Foundation of China (16CGL033); Funding Program for High-level Talents of Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality of China (CIT&TCD201704033).

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Authors and Affiliations

  1. Beijing Technology and Business University, Haidian, Beijing, 100048, China

    Jing Wang & Haotian Liu

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  1. Jing Wang
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  2. Haotian Liu
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Correspondence to Jing Wang.

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Wang, J., Liu, H. Snow removal resource location and allocation optimization for urban road network recovery: a resilience perspective. J Ambient Intell Human Comput 10, 395–408 (2019). https://doi.org/10.1007/s12652-018-0717-3

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  • DOI: https://doi.org/10.1007/s12652-018-0717-3

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