Time Resource Networks
This work addresses scheduling challenges in domains like power management, but it appears incremental as it builds on existing temporal network representations.
The paper tackles the problem of scheduling under resource constraints, such as power management, by introducing Time Resource Networks (TRNs) as an encoding method, and proposes two algorithms (Mixed Integer Programming and Constraint Programming) for consistency determination, evaluated on scheduling problems with temporal constraints.
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.