Search Word(s) in Title, Keywords, Authors, and Abstract: Chanchan Zhao

Optimization of Train Working Plan based on Multiobjective Bi-level Programming Model
Xiaowei HAI and Chanchan ZHAO
Page: 487~498, Vol. 14, No.2, 2018
10.3745/JIPS.04.0066

Keywords: Bi-Level Programming, Genetic Algorithm, Multiobjective, Train Working Plan
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The purpose of the high-speed railway construction is to better satisfy passenger travel demands. Accordingly, the design of the train working plan must also take a full account of the interests of passengers. Aiming at problems, such as the complex transport organization and different speed trains coexisting, combined with the existing research on the train working plan optimization model, the multiobjective bi-level programming model of the high-speed railway passenger train working plan was established. This model considers the interests of passengers as the center and also takes into account the interests of railway transport enterprises. Specifically, passenger travel cost and travel time minimizations are both considered as the objectives of upper-level programming, whereas railway enterprise profit maximization is regarded as the objective of the lower-level programming. The model solution algorithm based on genetic algorithm was proposed. Through an example analysis, the feasibility and rationality of the model and algorithm were proved.


A New Approach for Hierarchical Dividing to Passenger Nodes in Passenger Dedicated Line
Chanchan Zhao, Feng Liu and Xiaowei Hai
Page: 694~708, Vol. 14, No.3, 2018
10.3745/JIPS.04.0074

Keywords: Hierarchical Dividing, K-Means, Passenger Nodes, Passenger Dedicated line, Self-Organizing Map
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China possesses a passenger dedicated line system of large scale, passenger flow intensity with uneven distribution, and passenger nodes with complicated relations. Consequently, the significance of passenger nodes shall be considered and the dissimilarity of passenger nodes shall be analyzed in compiling passenger train operation and conducting transportation allocation. For this purpose, the passenger nodes need to be hierarchically divided. Targeting at problems such as hierarchical dividing process vulnerable to subjective factors and local optimum in the current research, we propose a clustering approach based on self-organizing map (SOM) and k-means, and then, harnessing the new approach, hierarchical dividing of passenger dedicated line passenger nodes is effectuated. Specifically, objective passenger nodes parameters are selected and SOM is used to give a preliminary passenger nodes clustering firstly; secondly, Davies–Bouldin index is used to determine the number of clusters of the passenger nodes; and thirdly, k-means is used to conduct accurate clustering, thus getting the hierarchical dividing of passenger nodes. Through example analysis, the feasibility and rationality of the algorithm was proved.