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A genetic algorithm for multiobjective dangerous goods route planning

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Transportation of dangerous goods (DGs) can significantly affect human life and the environment if accidents occur during the transportation process. Therefore, safe DG transportation is of vital importance, especially in high-density living environments. Effective routing of DG shipments is thus essential to the lowering of risk associated with DG transportation. DG routing is inherently a multicriteria, multiobjective problem in which various factors, such as cost, safety, public and environmental exposure, need to be simultaneously considered. We develop in this paper a multiobjective genetic algorithm (MOGA) for the determination of optimal routes for DG transportation under conflicting objectives. Implemented within the geographical information system environment, the MOGA approach is applied to the transportation of liquefied petroleum gas in the road network of Hong Kong. Experimental results in this case study substantiate the conceptual arguments and demonstrate the good performance of the proposed approach.
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Keywords: GIS; dangerous goods transportation; genetic algorithm; multiobjective route planning

Document Type: Research Article

Affiliations: 1: Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong 2: Department of Geography and Resource Management, Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, NT, Hong Kong 3: Department of Geography and Resource Management, Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong

Publication date: June 1, 2013

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