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Synthetically improved genetic algorithm in stochastic programming model in public traffic dispatch system

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3 Author(s)
Lei Zhou ; Sch. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhang, China ; Hong-Qi Hui ; Bin Liu

Through the investigation and study this paper establishes a new scheduling model to the bus in solving driving timetable. In order to avoid the traditional scheduling model, this paper establishment of the model considering both interest of passengers and bus companies. Using stochastic analysis theory, programming theory and so on, we analyzed the bus scheduling and the problem of bus arrangement in Shijiazhuang. We establish a stochastic nonlinear programming model in bus scheduling problem. Through synthesizing effect function we change the stochastic nonlinear programming model to the normal programming model. Then this paper uses a synthetically improved genetic algorithm to solve this model. Through comparing, we find using synthesizing effect function on stochastic solve the stochastic programming in an easy way, and also can get a better solution. Then this paper uses this algorithm to solve the new scheduling model.

Published in:

Machine Learning and Cybernetics (ICMLC), 2010 International Conference on  (Volume:3 )

Date of Conference:

11-14 July 2010