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This comprehensive and clearly structured book presents essential information on modern Location Science. The book is divided into three parts: basic concepts, advanced concepts and applications. Written by the most respected specialists in the field and thoroughly reviewed by the editors, it first lays out the fundamental problems in Location Science and provides the reader with basic background information on location theory. Part II covers advanced models and concepts, broadening and expanding on the content presented in Part I. It provides the reader with important tools to help them understand and solve real-world location problems. Part III is dedicated to linking Location Science with other areas like GIS, telecommunications, healthcare, rapid transit networks, districting problems and disaster events, presenting a wide range of applications. This part enables the reader to understand the role of facility location in such areas, as well as to learn how to handle realistic location problems. The book is intended for researchers working on theory and applications involving location problems and models. It is also suitable as a textbook for graduate courses on facility location.
This book constitutes the thoroughly refereed proceedings of the 8th International Conference on Data Management Technologies and Applications, DATA 2019, held in Prague, Czech Republic, in July 2019. The 8 revised full papers were carefully reviewed and selected from 90 submissions. The papers deal with the following topics: decision support systems, data analytics, data and information quality, digital rights management, big data, knowledge management, ontology engineering, digital libraries, mobile databases, object-oriented database systems, and data integrity.
Telecommunications - central to our daily lives - continues to change dramatically. These changes are the result of technological advances, deregulation, the proliferation of broadband service offers, and the spectacular popularity of the Internet and wireless services. In such adynamic technological and economic environment, competition is increasing among service providers and among equipment manufacturers. Consequently, optimization of the planning process is becoming essential. Although telecommunications network planning has been tackled by the Operations Research community for some time, many fundamental problems remain challenging. Through its fourteen chapters, this book covers some new and some still challenging older problems which arise in the planning of telecommunication networks. Telecommunications Network Planning will benefit both telecommunications practitioners looking for efficient methods to solve their problems and operations researchers interested in telecommunications. The book examines network design and dimensioning problems; it explores Operation Research issues related to a new standard Asynchronous Transfer Mode (ATM); it overviews problems that arise when designing survivable SDH/SONET Networks; it considers some broadband network problems; and it concludes with three chapters on wireless and mobile networks. Leading area researchers have contributed their recent research on the telecommunications and network topics treated in the volume.
The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available. The scope of LNCS, including its subseries LNAI and LNBI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. In parallel to the printed book, each new volume is published electronically in LNCS Online.
We study three capacity expansion problems in contemporary long distance telecommunication networks. The first two problems, motivated by a major long distance provider, address capacity expansion in national hybrid long distance telecommunication networks that use both the traditional TDM technology and more recent VoIP technology to transport voice calls. While network capacity expansion in general is known to be hard to approximate, we exploit the unique requirements associated with hybrid networks to develop compact models and algorithms with strong performance guarantees for these problems. For a single period single facility capacity expansion problem in a hybrid network, using a decomposition approach we design a (2 + E)-factor approximation algorithm. Generalizing this idea, we propose a Decentralized Routing Scheme that can be used to design approximation algorithms for many variations of hybrid network capacity expansion. For the Survivable Capacity Expansion Problem in hybrid networks, in which we are required to install enough capacity to be able to support all demands even if a single link fails, we propose a compact integer program model. We show that this problem is APX-Hard, and present two heuristics with constant worst case performance guarantees. Finally, we consider the capacity planning problem when peak demands occurring at different times can share network capacity. We propose a general model for capturing time variation of demand, and establish a necessary and sufficient condition for a capacity plan to be feasible. Using a cutting plane approach, we develop a heuristic procedure. Computational experiments on real and random instances show that the proposed procedure performs well, producing solutions within 12% of optimality on average for the instances tested. The tests also highlight the significant savings potential that might be obtained by capacity planning with time sharing.
For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.
This book contains a key component of the NII 2000 project of the Computer Science and Telecommunications Board, a set of white papers that contributed to and complements the project's final report, The Unpredictable Certainty: Information Infrastructure Through 2000, which was published in the spring of 1996. That report was disseminated widely and was well received by its sponsors and a variety of audiences in government, industry, and academia. Constraints on staff time and availability delayed the publication of these white papers, which offer details on a number of issues and positions relating to the deployment of information infrastructure.