Bus Scheduling Optimization Based on Improved Strength Pareto

Bus Scheduling Problem involves conflictive objectives for bus agencies and passengers. To obtain solutions from this multi-objective problem, an optimizer SPEA2, was employed to provide a Pareto set of reliable bus schedules. The proposed approach was applied to a specific bus route using historical passenger flow data. The result obtained in this work was compared to the results provided by different optimization strategy in a quoted research, which was to solve a similar model with Immune Artificial Algorithm. Furthermore, the approach to execute real-time control was studied and an online platform was established to publish the bus transit information to improve service quality.

[1]  Shi Chen,et al.  A multi-objective model for regional bus timetable based on NSGA-II , 2012, 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE).

[2]  Mohamadreza Banihashemi,et al.  A comparative analysis of bus transit vehicle scheduling models , 2003 .

[3]  Shangyao Yan,et al.  A scheduling model and a solution algorithm for inter-city bus carriers , 2002 .

[4]  Ming Wei,et al.  Improved ant colony algorithm for multi-depot bus scheduling problem with route time constraints , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[5]  Tong Gang.  Application Study of Genetic Algorithm on Bus Scheduling , 2005 .

[6]  Mohamadreza Banihashemi,et al.  HEURISTIC APPROACHES FOR SOLVING LARGE-SCALE BUS TRANSIT VEHICLE SCHEDULING PROBLEM WITH ROUTE TIME CONSTRAINTS , 2002 .

[7]  Jing Wang,et al.  The optimization of bus scheduling based on genetic algorithm , 2011, Proceedings 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE).

[8]  Sutanto Soehodho Nahry.  Optimal scheduling of public transport fleet at network level , 2000 .

[9]  Shengchuan Zhao,et al.  Research on Bus Scheduling Based on Artificial Immune Algorithm , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[10]  Haode Liu,et al.  A Vehicle Scheduling Model and Efficient Algorithm for Single Bus Line , 2008, 2008 Workshop on Power Electronics and Intelligent Transportation System.

[11]  Mohammad Ali Abido,et al.  Multiobjective optimal power flow using Improved Strength Pareto Evolutionary Algorithm (SPEA2) , 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

[12]  Nigel H. M. Wilson,et al.  THE REAL-TIME DEADHEADING PROBLEM IN TRANSIT OPERATIONS CONTROL , 1998 .

[13]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[14]  Malachy Carey.  Optimizing scheduled times, allowing for behavioural response , 1998 .