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Study on Macroscopical Layout Optimization Model of Large Passenger Transfer Hub Facilities Based on NSGA-II

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Intelligent Interactive Multimedia Systems and Services (KES-IIMSS-18 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 98))

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Abstract

In general, large passenger hubs contain a variety of transportation functional areas. The facility configuration requirements of different functional areas are not the same, and a rational collocation of spatial positions and the number of functional areas will greatly improve the level of service. By analyzing the connotations of the functional area, an optimization objective function was built, based on the average expected passenger walking time, average cross-collision delays [average delay due to collisions between passengers moving in opposing directions] of passengers, and the cost of the hub, with constraint conditions on functional acreage, shape and location, as well as a model of macroscopical layout optimization of hub facilities. A variety of optimization problem-solving methods were compared, and given the features of this model, the genetic algorithm NSGA-II was selected. Finally, this paper gives an example of a three-storey high-speed rail hub, evaluates the hub’s layout scheme, and proves that the model is effective and feasible. Therefore, the research results can be used to evaluate the layout plans of passenger transfer facilities for large hubs, and provide a theoretical foundation for perfecting hub transfer facilities.

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Acknowledgement

This research was financed by the Natural Science Foundation of Zhejiang (No. LY18G030021 & No. LY18E080021).

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Correspondence to Chengyuan Mao .

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Mao, C., Bie, Y., Zhou, K., Qi, W. (2019). Study on Macroscopical Layout Optimization Model of Large Passenger Transfer Hub Facilities Based on NSGA-II. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L., Vlacic, L. (eds) Intelligent Interactive Multimedia Systems and Services. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-319-92231-7_40

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