Optimization of Train Working Plan based on Multiobjective Bi-level Programming Model
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초록
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 atproblems, such as the complex transport organization and different speed trains coexisting, combined withthe existing research on the train working plan optimization model, the multiobjective bi-level programmingmodel of the high-speed railway passenger train working plan was established. This model considers theinterests 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 ofupper-level programming, whereas railway enterprise profit maximization is regarded as the objective of thelower-level programming. The model solution algorithm based on genetic algorithm was proposed. Throughan example analysis, the feasibility and rationality of the model and algorithm were proved.
Abstract
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 atproblems, such as the complex transport organization and different speed trains coexisting, combined withthe existing research on the train working plan optimization model, the multiobjective bi-level programmingmodel of the high-speed railway passenger train working plan was established. This model considers theinterests 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 ofupper-level programming, whereas railway enterprise profit maximization is regarded as the objective of thelower-level programming. The model solution algorithm based on genetic algorithm was proposed. Throughan example analysis, the feasibility and rationality of the model and algorithm were proved.
참고문헌 (12)
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