Maintenance and marginal cost analysis of a two-unit cold standby system

Ankara : Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent University, 1997.Thesis (Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 97-102.The Marginal Cost Analysis (MCA) of maintenance policies is a concept gaining interest in the recent years. This approach, due to Berg, has been categorized as an Economics Oriented Approach, as different from the classical probability centered approach. The MCA has been successfully applied to the Age Replacement and the Block Replacement policies, and was shown to be flexible enough to permit extensions and generalizations. In this thesis, we apply the MCA approach to a more complex model. We consider a two-unit cold standby system. Upon failure of the working unit in the time interval [0,T) the unit is replaced by the standby unit if available. If the standby unit is in repair, the system is down, and a downtime cost is incurred. The item inspected at time T is in one of two states: “good” , or “critical” . The good unit continues operation, whereas a unit in critical state is sent to repair. The switchover is immediate. We derive and compare the marginal cost function as well as the long-run cost per unit time function.Hamdaoui, ChokriM.S

Optimization based methods for solving some problems in telecommunications and the internet

The purpose of this thesis is to develop some new algorithms based on optimization techniques for solving some problems in some areas of telecommunications and the Internet. There are two main parts to this thesis. In the first part we discuss optimization based stochastic and queueing models in telecommunications network corrective maintenance. In the second part we develop optimization based clustering (OBC) algorithms for network evolution and multicast routing. The most typical scenario encountered during mathematical optimization modelling in telecommunications, for example, is to minimize the cost of establishment and maintenance of the networks subject to the performance constraints of the networks and the reliability constraints of the networks as well. Most of these optimization problems are global optimization, that is, they have many local minima and most of these local minima do not provide any useful information for solving these problems. Therefore, the development of effective methods for solving such global optimization problems is important. To run the telecommunications networks with cost-effective network maintenance,we need to establish a practical maintenance model and optimize it. In the first part of the thesis, we solve a known stochastic programming maintenance optimization model with a direct method and then develop some new models. After that we introduce queue programming models in telecommunications network maintenance optimization. The ideas of profit, loss, and penalty will help telecommunications companies have a good view of their maintenance policies and help them improve their service. In the second part of this thesis we propose the use of optimization based clustering (OBC) algorithms to determine level-constrained hierarchical trees for network evolution and multicast routing. This problem is formulated as an optimization problem with a non-smooth, non-convex objective function. Different algorithms are examined for solving this problem. Results of numerical experiments using some artifiicial and real-world databases are reported.Doctor of Philosoph

Stochastic Processes with Applications

Stochastic processes have wide relevance in mathematics both for theoretical aspects and for their numerous real-world applications in various domains. They represent a very active research field which is attracting the growing interest of scientists from a range of disciplines.This Special Issue aims to present a collection of current contributions concerning various topics related to stochastic processes and their applications. In particular, the focus here is on applications of stochastic processes as models of dynamic phenomena in research areas certain to be of interest, such as economics, statistical physics, queuing theory, biology, theoretical neurobiology, and reliability theory. Various contributions dealing with theoretical issues on stochastic processes are also included

Preserving the Quality of Architectural Tactics in Source Code

In any complex software system, strong interdependencies exist between requirements and software architecture. Requirements drive architectural choices while also being constrained by the existing architecture and by what is economically feasible. This makes it advisable to concurrently specify the requirements, to devise and compare alternative architectural design solutions, and ultimately to make a series of design decisions in order to satisfy each of the quality concerns. Unfortunately, anecdotal evidence has shown that architectural knowledge tends to be tacit in nature, stored in the heads of people, and lost over time. Therefore, developers often lack comprehensive knowledge of underlying architectural design decisions and inadvertently degrade the quality of the architecture while performing maintenance activities. In practice, this problem can be addressed through preserving the relationships between the requirements, architectural design decisions and their implementations in the source code, and then using this information to keep developers aware of critical architectural aspects of the code. This dissertation presents a novel approach that utilizes machine learning techniques to recover and preserve the relationships between architecturally significant requirements, architectural decisions and their realizations in the implemented code. Our approach for recovering architectural decisions includes the two primary stages of training and classification. In the first stage, the classifier is trained using code snippets of different architectural decisions collected from various software systems. During this phase, the classifier learns the terms that developers typically use to implement each architectural decision. These ``indicator terms\u27\u27 represent method names, variable names, comments, or the development APIs that developers inevitably use to implement various architectural decisions. A probabilistic weight is then computed for each potential indicator term with respect to each type of architectural decision. The weight estimates how strongly an indicator term represents a specific architectural tactics/decisions. For example, a term such as \emph{pulse} is highly representative of the heartbeat tactic but occurs infrequently in the authentication. After learning the indicator terms, the classifier can compute the likelihood that any given source file implements a specific architectural decision. The classifier was evaluated through several different experiments including classical cross-validation over code snippets of 50 open source projects and on the entire source code of a large scale software system. Results showed that classifier can reliably recognize a wide range of architectural decisions. The technique introduced in this dissertation is used to develop the Archie tool suite. Archie is a plug-in for Eclipse and is designed to detect wide range of architectural design decisions in the code and to protect them from potential degradation during maintenance activities. It has several features for performing change impact analysis of architectural concerns at both the code and design level and proactively keep developers informed of underlying architectural decisions during maintenance activities. Archie is at the stage of technology transfer at the US Department of Homeland Security where it is purely used to detect and monitor security choices. Furthermore, this outcome is integrated into the Department of Homeland Security\u27s Software Assurance Market Place (SWAMP) to advance research and development of secure software systems

Orbital Debris: A Chronology

This chronology covers the 37-year history of orbital debris concerns. It tracks orbital debris hazard creation, research, observation, experimentation, management, mitigation, protection, and policy. Included are debris-producing, events; U.N. orbital debris treaties, Space Shuttle and space station orbital debris issues; ASAT tests; milestones in theory and modeling; uncontrolled reentries; detection system development; shielding development; geosynchronous debris issues, including reboost policies: returned surfaces studies, seminar papers reports, conferences, and studies; the increasing effect of space activities on astronomy; and growing international awareness of the near-Earth environment

First International Conference on Ada (R) Programming Language Applications for the NASA Space Station, volume 2

Topics discussed include: reusability; mission critical issues; run time; expert systems; language issues; life cycle issues; software tools; and computers for Ada

Integrated Systems Control in the Steel Industry. State-of-the-Art Review and Proceedings of the Conference June 30-July 2, 1975

Integrated systems control has as its goal the integration of the information processing, decision-making and control functions of an industrial system to achieve increased operating efficiency and productivity, better utilization of resources, improved product quality and other benefits. As the steel industry is well advanced, relative to other industries, in the application of highly computerized systems integration, it was selected as the basis for a first case study. The Review presents both the results of a state-of-the-art survey of integrated systems control in the steel industry and the proceedings of a IIASA conference on the subject. The results motivate a general methodology for integrated control system design based on a hierarchical structuring of the system, incorporating multilevel decomposition and temporal and functional multilayer concepts