Auf der Grundlage einer Stichprobe von 105 sächsischen Unternehmen wird deren Zukunftsfähigkeit mit Hilfe einer neuen Ratingtechnologie analysiert. Diese basiert - neben klassischen Analysewerkzeugen - auf einer direkten Einbeziehung von Risikogesichtspunkten und einer stochastischen...

We provide results for an efficient analytical valuation of partial moments of the multivariate Gaussian distribution over convex polyhedrons to aid the solution, sensitivity analysis and structural analysis of a large number of two-stage resource acquisition and allocation problems. These...

The paper is concerned with the reduction of a class of stochastic optimal control problems to simpler problems by using decomposition and aggregation. Decomposition is shown to provide a good approximation when the system dynamics involve nearly decomposable matrices or variables with strong...

In this paper, we identify a new class of stochastic Iinear convex optimal control problems, whose solution can be obtained by solving appropriate equivalent deterministic optimal control problems. The term 'linear convex' is meant to imply that the dynamics is linear and the cost function is...

This paper presents an extension of earlier research on heirarchical control of stochastic manufacturing systems with linear production costs. A new method is introduced to construct asymptotically optimal open-loop and feedback controls for manufacturing systems in which the rates of machine...

This paper is concerned with an asymptotic analysis of hierarchical production and setup scheduling in a stochastic manufacturing system consisting of a single failure-prone machine and facing constant demands for a number of products. At any given time the system can only produce one type of...

In this paper, we treat an optimal control problem of a stochastic two-machine flowshop with machines subject to random breakdown and repair. While the problem is difficult to solve, it can be approximated by a deterministic problem when the rates of machine failure and repair become large....

We consider an N-machine flowshop with unreliable machines and bounds on work-in-process. Machine capacities and demand processes are finite-state Markov chains. The problem is to choose the rates of production on the machines over time to minimize the expected discounted costs of production and...

We present some insights obtained from the considerable research that has accumulated in proving that a hierarchical decomposition based on the frequencies of occurence of different types of events in the system results in near-optimal decisions as the rates of some events become large compared...

This paper deals with an asymptotic analysis of hierarchical production planning in stochastic manufacturing systems consisting of a single or parallel failure-prone machines producing a number of different products without attrition. The objective is to choose production rates over time in...