Publisher Summary This chapter reviews a survey on the operations research literature
applied to the domain of public transit, with a focus on recent contributions. It highlights a …

Organizations need to focus on many parameters to reach their goals such as personnel
satisfaction at the top level, profit maximization, increasing system efficiency and minimizing …

Column generation (CG) is widely used for solving large-scale optimization problems. This
article presents a new approach based on a machine learning (ML) technique to accelerate …

Computational methods for rostering and personnel scheduling has been a subject of
continued research and commercial interest since the 1950s. This annotated bibliography …

This paper presents an exact approach for solving the simultaneous vehicle and crew
scheduling problem in urban mass transit systems. We consider the single depot case with a …

This paper deals with models, relaxations, and algorithms for an integrated approach to
vehicle and crew scheduling for an urban mass transit system with a single depot. We …

This paper presents two different models and algorithms for integrated vehicle and crew
scheduling in the multiple-depot case. The algorithms are both based on a combination of …

One of the things I knew for sure when I graduated in 2003 was that I didn't want to do a PhD
research. After my study I really wanted to jump into the real world to solve real problems. At …

Column generation is often used to solve problems involving set-partitioning constraints,
such as vehicle-routing and crew-scheduling problems. When these constraints are in large …

Column generation is an iterative method used to solve a variety of optimization problems. It
decomposes the problem into two parts: a master problem and one or more pricing …