Investigating Large Neighbourhood Search for Bus Driver Scheduling

Tommaso Mannelli Mazzoli, Lucas Kletzander, Pascal Van Hentenryck, Nysret Musliu

Keywords: Metaheuristics, Scheduling, Branch and Price, Bus Driver Scheduling, Transportation

TL;DR: We propose a new Large Neighbourhood Search for Bus Driver Scheduling based on novel destroy operators and Column Generation, which outperforms all previous methods on larger instances

Abstract:

The Bus Driver Scheduling Problem (BDSP) is a combinatorial optimisation problem with high practical relevance. The aim is to assign bus drivers to predetermined routes while minimising a specified objective function that considers operating costs as well as employee satisfaction. Since we must satisfy several rules from a collective agreement and European regulations, the BDSP is highly constrained. Hence, using exact methods to solve large real-life-based instances is computationally too expensive, while heuristic methods still have a considerable gap to the optimum.
Our paper presents a Large Neighbourhood Search (LNS) approach to solve the BDSP. We propose several novel destroy operators and an approach using column generation to repair the sub-problem.
We analyse the impact of the destroy and repair operators and investigate various possibilities to select them, including adaptivity.
The proposed approach improves all the upper bounds for larger instances that exact methods cannot solve, as well as for some mid-sized instances, and outperforms existing heuristic approaches for this problem on all benchmark instances.

Primary Keywords: Applications

Category: Long

Student: Graduate

Submission Number: 131