pith. sign in

arxiv: 1503.03974 · v3 · pith:G4VBFJYCnew · submitted 2015-03-13 · 💻 cs.DS · cs.AI

Hyper Temporal Networks

classification 💻 cs.DS cs.AI
keywords temporalconstraintshytnsstnsdelayhypernetworksconjunctions
0
0 comments X
read the original abstract

Simple Temporal Networks (STNs) provide a powerful and general tool for representing conjunctions of maximum delay constraints over ordered pairs of temporal variables. In this paper we introduce Hyper Temporal Networks (HyTNs), a strict generalization of STNs, to overcome the limitation of considering only conjunctions of constraints but maintaining a practical efficiency in the consistency check of the instances. In a Hyper Temporal Network a single temporal hyperarc constraint may be defined as a set of two or more maximum delay constraints which is satisfied when at least one of these delay constraints is satisfied. HyTNs are meant as a light generalization of STNs offering an interesting compromise. On one side, there exist practical pseudo-polynomial time algorithms for checking consistency and computing feasible schedules for HyTNs. On the other side, HyTNs offer a more powerful model accommodating natural constraints that cannot be expressed by STNs like Trigger off exactly delta min before (after) the occurrence of the first (last) event in a set., which are used to represent synchronization events in some process aware information systems/workflow models proposed in the literature.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.