Time Resource Networks

TL;DR

This paper introduces the Time Resource Network (TRN), a new framework for modeling resource-constrained scheduling problems with continuous temporal and resource constraints, and proposes algorithms for checking their consistency.

Contribution

The paper presents the TRN framework that unifies various temporal constraint models with resource constraints and offers two algorithms for consistency checking.

Findings

Algorithms successfully evaluate scheduling problems with temporal and resource constraints.

TRN effectively models power management and similar resource-constrained scheduling scenarios.

Constraint programming and mixed integer programming approaches are effective for TRN consistency.

Abstract

The problem of scheduling under resource constraints is widely applicable. One prominent example is power management, in which we have a limited continuous supply of power but must schedule a number of power-consuming tasks. Such problems feature tightly coupled continuous resource constraints and continuous temporal constraints. We address such problems by introducing the Time Resource Network (TRN), an encoding for resource-constrained scheduling problems. The definition allows temporal specifications using a general family of representations derived from the Simple Temporal network, including the Simple Temporal Network with Uncertainty, and the probabilistic Simple Temporal Network (Fang et al. (2014)). We propose two algorithms for determining the consistency of a TRN: one based on Mixed Integer Programing and the other one based on Constraint Programming, which we evaluate on scheduling problems with Simple Temporal Constraints and Probabilistic Temporal Constraints.