We study the problem of scheduling a chain-reentrant shop, a shop in which each job goes for its processing rst to a machine called the primary machine, then to a number of other machines in a xed sequence, and nally back to the primary machine for its last operation. The problem is to schedule the jobs so as to minimize the makespan. This problem is NP-hard in the strong sense for a general number of machines. We focus in particular on the two-machine case that is also NP-hard at least in the ordinary sense. We prove some properties that identify a speci c class of optimal schedules, and then use these properties in designing an approximation algorithm and a branchand-bound type optimization algorithm. The approximation algorithm, of which we present three versions, has a worst-case performance guarantee of 3=2 along with an excellent empirical performance. The optimization algorithm solves large instances quickly. Finally, we identify a few well solvable special cases and present a pseudopolynomial algorithm for the case in which the rst and the last operations of any job (on the primary machine) are identical.

iMAT is a system of automatic medication dispensers and software tools. It is for people who take medications on long term basis at home to stay well and independent. The system helps its users to improve rigor in compliance by preventing misunderstanding of medication directions and making medication schedules more tolerant to tardiness and negligence. This paper presents an overview of the assumptions, models, architecture and implementation of the system.