In this survey we review methods to analyze open queueing network models for discrete manufacturing systems. We focus on design and planning models for job shops. The survey is divided in two parts: in the first we review exact and approximate decomposition methods for performance evaluation models for single and multiple product class networks. The second part reviews optimization models of th...

This paper describes a simple complete search for cumulative scheduling based on the detection and resolution of minimal critical sets (MCS). The heuristic for selecting MCSs relies on an estimation of the related reduction of the search space. An extension of the search procedure using selfadapting shaving is proposed. The approach was implemented on top of classical constraint propagation alg...

We study algorithmic problems in multi-stage open shop processing systems that are centered around reachability and deadlock detection questions. We characterize safe and unsafe system states. We show that it is easy to recognize system states that can be reached from the initial state (where the system is empty), but that in general it is hard to decide whether one given system state is reacha...

We study algorithmic problems in multi-stage open shop processing systems that are centered around reachability and deadlock detection questions. We characterize safe and unsafe system states. We show that it is easy to recognize system states that can be reached from the initial state (where the system is empty), but that in general it is hard to decide whether one given system state is reacha...

The Affordable Care Act (ACA) dramatically expanded the use of regulated marketplaces in health insurance, but consumers often fail to shop for plans during open enrollment periods. Typically these consumers are automatically reenrolled in their old plans, which potentially exposes them to unexpected increases in their insurance premiums and cost sharing. We conducted a randomized intervention ...

This paper studies the complexity variations of scheduling problems in diierent machine environments when replacing operations with arbitrary processing times by the chains of operations with unit processing times. Special attention is paid to polynomial-time algorithms for chain-like precedence-constrained problems with unit processing times and transformations of their solutions to each other...

The Group Shop Scheduling Problem (GSP) is a generalization of the classical Job Shop and Open Shop Scheduling Problems. In the GSP there are m machines and n jobs. Each job consists of a set of operations, which must be processed on specified machines without preemption. The operations of each job are partitioned into groups on which a total precedence order is given. The problem is to order t...

We present Bar Systems: a family of very simple algorithms for different classes of complex optimization problems in static and dynamic environments by means of reactive multi agent systems. Bar Systems are in the same line as other Swarm Intelligence algorithms; they are loosely inspired in the behavior a staff of bartenders can show while serving drinks to a crowd of customers in a bar or pub...

The specific goal of this paper is to present an efficient heuristic for n-jobs, two machine open shop scheduling involving job block criteria and weights of jobs due to their relative importance, under the condition when probabilities are associate with processing time to obtain an optimal or near optimal sequence which minimize the makespan. The proposed heuristic developed in this paper is s...