Capacity planning decisions affect a significant portion of future revenue. In the semiconductor industry, they need to be made in the presence of both highly volatile demand and long capacity installation lead-times. In contrast to traditional discrete-time models, we present a continuous-time stochastic programming model for multiple resource types and product families. We show how this appro...

This paper discusses the development and testing of simulation software for the measurement and modeling of UNIX performance data for data centers with mission-critical UNIX servers. The emphasis is on sizing CPU resources and assumes well configured Memory and Disk I/O subsystems. We begin by ensuring that our simulation package can be verified against the available theory on the subject, then...

Process planning in the automotive industry is referred to as advance manufacturing engineering, because it is done in advance of production — before the facilities are created. When developing these processes, simulation is typically done by service groups, not the process planner, resulting in communication errors and unnecessary iterations. Software applications are now becoming available th...

The design of survivable mesh based STM networks has received considerable attention in recent years and is a complex multiconstraint optimization problem. In this paper, a new spare capacity planning methodology is proposed utilizing genetic algorithms. The method is based on forcing flows/traffic which are on paths that are disjoint to share backup spare capacity. The major advantages of the ...

Discrete event simulation models coupled with statistical analysiS allow you to select a system design or resource configuration with a high degree of certainty. This paper Introduces discrete event simulation and demonstrates the use of response surtace methodology to select a resource configuration. The example system Is kept intentionally generic to emphasize the applicability of this method...

The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for...

We report on an application of data envelopment analysis to hospital capacity planning in Germany. This work was carried out as part of a ministry report prepared by a major German health care consulting company. Our input into this report is a first attempt to incorporate the relative economic efficiency of hospitals into the capacity planning process. The application develops a general approa...

Vertical search engines focus on specific slices of content, such as the Web of a single country or the document collection of a large corporation. Despite this, like general open web search engines, they are expensive to maintain, expensive to operate, and hard to design. Because of this, predicting the response time of a vertical search engine is usually done empirically through experimentati...

The proliferation of client–server systems in business continues unabated, as applications are split into local tasks run on ‘client’ workstations and resource-intensive computations run on a ‘server’ mainframe. The complexity of such systems requires quantitative modelling for their efficient design and reconfiguration throughout their lifetime. The tools and techniques that are needed for the...