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- 저자 : Shuaian Wang (검색결과 2 건)
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Rural Bus Route Design Problem: Model Development and Case Studies
Shuaian Wang,Xiaobo Qu 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.6
Rural and suburban areas have a low density of population. The bus services for these areas have unique features such as no transfer exists as there is only one bus route for each area and nearly all passengers travel to the same destination of city center. These features make the design of suburban bus route a practical and interesting research topic. We formulate such a suburban bus route design problem as an optimization model. We subsequently prove that the problem is NP-hard. In view of the problem structure, a dynamic programming approach is developed to obtain the optimal solution efficiently for practical-size problems. The optimal solution contains information on which one of the two bus stops on both sides of a street to visit and the sequence of visiting the chosen bus stops. Two case studies based on a square-block example and a suburb in Australia are carried out to demonstrate the applicability of the proposed model and method.
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Network-level Optimization of Bus Stop Placement in Urban Areas
Jingxu Chen,Shuaian Wang,Zhiyuan Liu,Xuewu Chen 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.4
Bus stops provide accessibility to public transit service, whereas they also influence the efficiency of mobility due to the extradwell time. The decision of bus stop locations is a tradeoff between access coverage and mobility. This paper formulates a biobjectiveoptimization model of bus stop placement problem at the network level. Two objectives are pertinent to the improvement ofmobility: minimization of total dwell time at stops and minimization of total number of bus stops. Access coverage is constrained toensure a certain level of accessibility. The issue of stop congestion and its effect on road traffic flow is also considered in the model. The model is applied to a case study of the bus network in urban areas of Yancheng, China. The results show that the proposed modelcan be efficiently solved by CPLEX to obtain Pareto optimal solutions for real-case problems.
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