1520. Optimizing shift assignments for tramway operations: a mixed-integer linear programming approach to generate fair and efficient solutions on large scale instances.
Invited abstract in session MC-7: Mathematical Programming in Scheduling, stream Scheduling and Project Management.
Monday, 12:30-14:00Room: Clarendon GR.01
Authors (first author is the speaker)
| 1. | Nathan Lainé
|
| Data & Optimization, Artelys |
Abstract
Shift assignment is a critical challenge for public transport operators, impacting both operational efficiency and workforce well-being. To enhance working conditions while maintaining high service quality, the Parisian public transport system operator RATP Group collaborated with Artelys to develop an optimization-based shift assignment module for tramway operations. This module efficiently allocates shifts (driving shifts, shifts related to passenger information, flow channeling, …) and time-offs using a mixed-integer linear programming approach. The case study highlights how Artelys leveraged a decomposition technique to generate fair and efficient assignments, enhancing both workforce well-being and operational performance in large-scale (assignments on a year for hundred agents) multi-objective scenarios (fairness between agents and multiple well-being criteria). Implemented with FICO XPRESS, this solution demonstrates how optimization can significantly improve manual assignment processes, offering valuable insights for transport planning and workforce management.
Keywords
- Scheduling
- Programming, Linear
- Programming, Multi-Objective
Status: accepted
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