Marc E. Posner

TL;DR: It is proved that the recognition version of this problem is NP-complete in the ordinary sense, and a computationally efficient dynamic programming algorithm is presented that is polynomially solvable.

TL;DR: A generation scheme for precedence constraints that achieves a target density which is uniform in the precedence constraint graph and a generation scheme that explicitly considers the correlation of routings in a job shop is presented.

TL;DR: This work shows that even when an optimal number of sensor nodes has been deployed randomly, statistical redundancy can be exploited to extend the network lifetime by up to seven times, and uses simulation to show that the assumption of homogeneous lifetime can result in severe loss of network lifetime.

TL;DR: This paper discusses the periodic job shop scheduling problem, a problem where an identical mixture of items, called a minimal part set MPS, is repetitively produced, and establishes that there exists a class of schedules that minimizes cycle time and repeats an identical timing pattern every MPS.

TL;DR: This paper represents a first attempt at a systematic study of sensitivity analysis for scheduling problems and identifies scheduling problems where performing additional or different computations during optimization facilitates sensitivity analysis.