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Snow removal resource location and allocation optimization for urban road network recovery: a resilience perspective
by
Liu, Haotian
, Wang, Jing
in
Artificial Intelligence
/ Cities
/ Computational Intelligence
/ Decision making
/ Electricity distribution
/ Emergencies
/ Engineering
/ Infrastructure
/ Mathematical models
/ Meteorological data
/ Optimization
/ Original Research
/ Recovery
/ Resilience
/ Roads & highways
/ Robotics and Automation
/ Search algorithms
/ Snow removal
/ Tabu search
/ Traffic
/ Traffic management
/ User Interfaces and Human Computer Interaction
/ Vehicle routing
2019
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Snow removal resource location and allocation optimization for urban road network recovery: a resilience perspective
by
Liu, Haotian
, Wang, Jing
in
Artificial Intelligence
/ Cities
/ Computational Intelligence
/ Decision making
/ Electricity distribution
/ Emergencies
/ Engineering
/ Infrastructure
/ Mathematical models
/ Meteorological data
/ Optimization
/ Original Research
/ Recovery
/ Resilience
/ Roads & highways
/ Robotics and Automation
/ Search algorithms
/ Snow removal
/ Tabu search
/ Traffic
/ Traffic management
/ User Interfaces and Human Computer Interaction
/ Vehicle routing
2019
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Do you wish to request the book?
Snow removal resource location and allocation optimization for urban road network recovery: a resilience perspective
by
Liu, Haotian
, Wang, Jing
in
Artificial Intelligence
/ Cities
/ Computational Intelligence
/ Decision making
/ Electricity distribution
/ Emergencies
/ Engineering
/ Infrastructure
/ Mathematical models
/ Meteorological data
/ Optimization
/ Original Research
/ Recovery
/ Resilience
/ Roads & highways
/ Robotics and Automation
/ Search algorithms
/ Snow removal
/ Tabu search
/ Traffic
/ Traffic management
/ User Interfaces and Human Computer Interaction
/ Vehicle routing
2019
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Snow removal resource location and allocation optimization for urban road network recovery: a resilience perspective
Journal Article
Snow removal resource location and allocation optimization for urban road network recovery: a resilience perspective
2019
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Overview
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.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
Subject
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