Graphs and algorithms
Polyhedral characterization of discrete dynamic programming
Operations Research
Directed hypergraphs and applications
Discrete Applied Mathematics - Special issue: combinatorial structures and algorithms
Mathematical Programming: Series A and B
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
Railway Timetabling Using Lagrangian Relaxation
Transportation Science
Modeling and Solving the Train Timetabling Problem
Operations Research
A Strategic Flow Model of Traffic Assignment in Static Capacitated Networks
Operations Research
Hypergraph partitioning for automatic memory hierarchy management
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Journal of Scheduling
Reordering and Local Rerouting Strategies to Manage Train Traffic in Real Time
Transportation Science
A Lagrangian heuristic algorithm for a real-world train timetabling problem
Discrete Applied Mathematics - Special issue: IV ALIO/EURO workshop on applied combinatorial optimization
Combinatorial Optimization: Theory and Algorithms
Combinatorial Optimization: Theory and Algorithms
| Hi-index | 0.00 |
Discrete time dynamic graphs are frequently used to model multicommodity flows or activity paths through constrained resources, but simple graphs fail to capture the interaction effects of resource transitions. The resulting schedules are not operationally feasible, and return inflated objective values. A directed hypergraph formulation is derived to address railway network sequencing constraints, and an experimental problem sample solved to estimate the magnitude of objective inflation when interaction effects are ignored. The model is used to demonstrate the value of advance scheduling of train paths on a busy North American railway.