Train Scheduling with Hybrid Answer Set Programming
  We present a solution to real-world train scheduling problems, involving
routing, scheduling, and optimization, based on Answer Set Programming (ASP).
To this end, we pursue a hybrid approach that extends ASP with difference
constraints to account for a fine-grained timing. More precisely, we
exemplarily show how the hybrid ASP system clingo[DL] can be used to tackle
demanding planning-and-scheduling problems. In particular, we investigate how
to boost performance by combining distinct ASP solving techniques, such as
approximations and heuristics, with preprocessing and encoding techniques for
tackling large-scale, real-world train scheduling instances. Under
consideration in Theory and Practice of Logic Programming (TPLP)
