Operations Research Letters

File contains problem instances reported in our work.

Aggregate data for: Decision Diagrams for Solving Traveling Salesman Problems with Pickup and Delivery in Real Time

Matlab code that generates Figure 1.b in paper "Optimality of an Affine Intensity Policy for Maximizing the Probability of an Arrival Count in Point-Process Intensity Control"

This is a repository containing the code used for the article A Fast Exact Pricing Algorithm for the Railway Crew Scheduling Problem'. In this article, a new exact pricing algorithm is proposed, and this algorithm is compared to the fastest known exact algorithm from literature. Abstract The railway crew scheduling problem consists of selecting a least cost set of duties that cover all tasks. Large-scale crew scheduling problems are typically solved with column generation, where in each iteration a pricing problem needs to be solved. When the duty constraints consist in a maximum duty length, a meal break constraint, and the requirement to start and end at the same crew depot, the fastest known exact pricing algorithm has O(|N|3) complexity, |N| being the number of tasks. In this work we propose an O(|N|2) exact pricing algorithm. We compare the two algorithms on randomly generated instances and show that a reduction in computation time of 95% is attained on instances of size |N|=1,250.

This is a repository containing the code used for the article A Fast Exact Pricing Algorithm for the Railway Crew Scheduling Problem'. In this article, a new exact pricing algorithm is proposed, and this algorithm is compared to the fastest known exact algorithm from literature. Abstract The railway crew scheduling problem consists of selecting a least cost set of duties that cover all tasks. Large-scale crew scheduling problems are typically solved with column generation, where in each iteration a pricing problem needs to be solved. When the duty constraints consist in a maximum duty length, a meal break constraint, and the requirement to start and end at the same crew depot, the fastest known exact pricing algorithm has O(|N|3) complexity, |N| being the number of tasks. In this work we propose an O(|N|2) exact pricing algorithm. We compare the two algorithms on randomly generated instances and show that a reduction in computation time of 95% is attained on instances of size |N|=1,250.