Development of decision support tool for optimizing urban emergency rescue facility locations to improve humanitarian logistics management
作者： Ming Zhao , Xiang Liu
DOI: 10.1016/J.SSCI.2017.10.007
关键词: Decision support system 、 Humanitarian Logistics 、 Process (engineering) 、 Optimization problem 、 Geospatial analysis 、 Engineering management 、 Management science 、 Work (electrical) 、 Workflow 、 Component (UML) 、 Engineering
摘要: Abstract Emergency rescue facility is an essential component of urban emergency logistics system, and selection their locations significant for public safety. Urban (UERFLs) problem essentially a geospatial multi-objective optimization (Geospatial-MOP), which presents challenge both researchers managers. In this study, user-friendly decision support tool was designed developed facilitating the process optimizing UERFLs in large-scale areas. We described design, architecture implementation its core component. Based on hypothetical case we introduced functionalities as well making workflow. The results provide evidences that can successfully generate Pareto-optimal frontier capture pool alternative solutions to maker trade-off. This work offers new insights promoting future management with use GIS emerging artificial intelligence technologies, makes contributions integrating algorithm solving problem.
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