A linear programming joint optimization model of overnight train timetabling and maintenance planning on high-speed...

Area of Science:

• Operations Research
• Transportation Engineering
• Railway Systems

Background:

• High-speed railway (HSR) maintenance is crucial for operational integrity.
• Overnight maintenance scheduling conflicts with overnight train operations.
• Existing planning methods often fail to integrate train timetabling and maintenance.

Purpose of the Study:

• To develop an integrated optimization model for joint train timetabling and maintenance planning on HSR.
• To address the conflict between overnight train operations and scheduled maintenance activities.
• To propose an efficient solution algorithm for practical HSR maintenance and scheduling.

Main Methods:

• Formulation of a mixed-integer linear programming model using linearization techniques (Big-M, binary state variables).
• Comparison and selection of minimum maintenance units (power supply sections over station sections).
• Development of an efficient solution algorithm by omitting station track constraints to manage computational complexity.

Main Results:

• The proposed model successfully integrates train operation and maintenance planning constraints.
• Normalization of objective functions for overnight trains and maintenance plans ensures balanced optimization.
• An efficient algorithm was developed and validated using real-world data from the Beijingxi-Guangzhounan HSR line.

Conclusions:

• The integrated optimization model provides an effective solution for joint HSR train timetabling and maintenance planning.
• The developed efficient algorithm addresses computational challenges, making the model practical for real-world applications.
• This research contributes to enhancing the operational efficiency and integrity of HSR systems through optimized overnight scheduling.