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Título : Approximation Methods for Polynomial Optimization : Models, Algorithms, and Applications Tipo de documento: documento electrónico Autores: Li, Zhening ; SpringerLink (Online service) ; He, Simai ; Zhang, Shuzhong Editorial: New York, NY : Springer New York Fecha de publicación: 2012 Otro editor: Imprint: Springer Colección: SpringerBriefs in Optimization, ISSN 2190-8354 Número de páginas: VIII, 124 p Il.: online resource ISBN/ISSN/DL: 978-1-4614-3984-4 Idioma : Inglés (eng) Palabras clave: Mathematics Applied mathematics Engineering Algorithms Mathematical models optimization Optimization Modeling and Industrial Applications of Clasificación: 51 Matemáticas Resumen: Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications. This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science Nota de contenido: 1. Introduction.-2. Polynomial over the Euclidean Ball -- 3. Extensions of the Constraint Sets -- 4. Applications -- 5. Concluding Remarks En línea: http://dx.doi.org/10.1007/978-1-4614-3984-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32828 Approximation Methods for Polynomial Optimization : Models, Algorithms, and Applications [documento electrónico] / Li, Zhening ; SpringerLink (Online service) ; He, Simai ; Zhang, Shuzhong . - New York, NY : Springer New York : Imprint: Springer, 2012 . - VIII, 124 p : online resource. - (SpringerBriefs in Optimization, ISSN 2190-8354) .
ISBN : 978-1-4614-3984-4
Idioma : Inglés (eng)
Palabras clave: Mathematics Applied mathematics Engineering Algorithms Mathematical models optimization Optimization Modeling and Industrial Applications of Clasificación: 51 Matemáticas Resumen: Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications. This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science Nota de contenido: 1. Introduction.-2. Polynomial over the Euclidean Ball -- 3. Extensions of the Constraint Sets -- 4. Applications -- 5. Concluding Remarks En línea: http://dx.doi.org/10.1007/978-1-4614-3984-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32828 Ejemplares
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Título : Data Correcting Approaches in Combinatorial Optimization Tipo de documento: documento electrónico Autores: Goldengorin, Boris ; SpringerLink (Online service) ; Pardalos, Panos M Editorial: New York, NY : Springer New York Fecha de publicación: 2012 Otro editor: Imprint: Springer Colección: SpringerBriefs in Optimization, ISSN 2190-8354 Número de páginas: X, 114 p. 41 illus Il.: online resource ISBN/ISSN/DL: 978-1-4614-5286-7 Idioma : Inglés (eng) Palabras clave: Mathematics Data structures (Computer science) Algorithms Mathematical optimization Graph theory Theory Optimization Structures Algorithm Analysis and Problem Complexity Clasificación: 51 Matemáticas Resumen: Data Correcting Approaches in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. Researches, students and engineers will benefit from new bounds and branching rules in development efficient branch-and-bound type computational algorithms. This book examines applications for solving the Traveling Salesman Problem and its variations, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems En línea: http://dx.doi.org/10.1007/978-1-4614-5286-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32852 Data Correcting Approaches in Combinatorial Optimization [documento electrónico] / Goldengorin, Boris ; SpringerLink (Online service) ; Pardalos, Panos M . - New York, NY : Springer New York : Imprint: Springer, 2012 . - X, 114 p. 41 illus : online resource. - (SpringerBriefs in Optimization, ISSN 2190-8354) .
ISBN : 978-1-4614-5286-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Data structures (Computer science) Algorithms Mathematical optimization Graph theory Theory Optimization Structures Algorithm Analysis and Problem Complexity Clasificación: 51 Matemáticas Resumen: Data Correcting Approaches in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. Researches, students and engineers will benefit from new bounds and branching rules in development efficient branch-and-bound type computational algorithms. This book examines applications for solving the Traveling Salesman Problem and its variations, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems En línea: http://dx.doi.org/10.1007/978-1-4614-5286-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32852 Ejemplares
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Título : Data Storage for Social Networks : A Socially Aware Approach Tipo de documento: documento electrónico Autores: Tran, Duc A ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2012 Otro editor: Imprint: Springer Colección: SpringerBriefs in Optimization, ISSN 2190-8354 Número de páginas: VIII, 47 p. 12 illus., 2 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-4636-1 Idioma : Inglés (eng) Palabras clave: Mathematics Database management Mathematical optimization Optimization Management Clasificación: 51 Matemáticas Resumen: Evidenced by the success of Facebook, Twitter, and LinkedIn, online social networks (OSNs) have become ubiquitous, offering novel ways for people to access information and communicate with each other. As the increasing popularity of social networking is undeniable, scalability is an important issue for any OSN that wants to serve a large number of users. Storing user data for the entire network on a single server can quickly lead to a bottleneck, and, consequently, more servers are needed to expand storage capacity and lower data request traffic per server. Adding more servers is just one step to address scalability. The next step is to determine how best to store the data across multiple servers. This problem has been widely-studied in the literature of distributed and database systems. OSNs, however, represent a different class of data systems. When a user spends time on a social network, the data mostly requested is her own and that of her friends; e.g., in Facebook or Twitter, these data are the status updates posted by herself as well as that posted by the friends. This so-called social locality should be taken into account when determining the server locations to store these data, so that when a user issues a read request, all its relevant data can be returned quickly and efficiently. Social locality is not a design factor in traditional storage systems where data requests are always processed independently. Even for today’s OSNs, social locality is not yet considered in their data partition schemes. These schemes rely on distributed hash tables (DHT), using consistent hashing to assign the users’ data to the servers. The random nature of DHT leads to weak social locality which has been shown to result in poor performance under heavy request loads. Data Storage for Social Networks: A Socially Aware Approach is aimed at reviewing the current literature of data storage for online social networks and discussing new methods that take into account social awareness in designing efficient data storage Nota de contenido: 1. Introduction (Amazon’s Dynamo, Google’s BigTable, Apache Cassandra).-2. Social Locality in Data Storage (Perfect vs. Imperfect Social Locality, Assumptions and Notations, Optimization Objectives, Multi-Objective Optimization) -- 3. S-PUT (Approach, Algorithm, Numerical Results, Notes) -- 4. S-CLONE (Approach, Algorithm, Numerical Results, Notes)- 5. Epilogue. –References En línea: http://dx.doi.org/10.1007/978-1-4614-4636-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32849 Data Storage for Social Networks : A Socially Aware Approach [documento electrónico] / Tran, Duc A ; SpringerLink (Online service) . - New York, NY : Springer New York : Imprint: Springer, 2012 . - VIII, 47 p. 12 illus., 2 illus. in color : online resource. - (SpringerBriefs in Optimization, ISSN 2190-8354) .
ISBN : 978-1-4614-4636-1
Idioma : Inglés (eng)
Palabras clave: Mathematics Database management Mathematical optimization Optimization Management Clasificación: 51 Matemáticas Resumen: Evidenced by the success of Facebook, Twitter, and LinkedIn, online social networks (OSNs) have become ubiquitous, offering novel ways for people to access information and communicate with each other. As the increasing popularity of social networking is undeniable, scalability is an important issue for any OSN that wants to serve a large number of users. Storing user data for the entire network on a single server can quickly lead to a bottleneck, and, consequently, more servers are needed to expand storage capacity and lower data request traffic per server. Adding more servers is just one step to address scalability. The next step is to determine how best to store the data across multiple servers. This problem has been widely-studied in the literature of distributed and database systems. OSNs, however, represent a different class of data systems. When a user spends time on a social network, the data mostly requested is her own and that of her friends; e.g., in Facebook or Twitter, these data are the status updates posted by herself as well as that posted by the friends. This so-called social locality should be taken into account when determining the server locations to store these data, so that when a user issues a read request, all its relevant data can be returned quickly and efficiently. Social locality is not a design factor in traditional storage systems where data requests are always processed independently. Even for today’s OSNs, social locality is not yet considered in their data partition schemes. These schemes rely on distributed hash tables (DHT), using consistent hashing to assign the users’ data to the servers. The random nature of DHT leads to weak social locality which has been shown to result in poor performance under heavy request loads. Data Storage for Social Networks: A Socially Aware Approach is aimed at reviewing the current literature of data storage for online social networks and discussing new methods that take into account social awareness in designing efficient data storage Nota de contenido: 1. Introduction (Amazon’s Dynamo, Google’s BigTable, Apache Cassandra).-2. Social Locality in Data Storage (Perfect vs. Imperfect Social Locality, Assumptions and Notations, Optimization Objectives, Multi-Objective Optimization) -- 3. S-PUT (Approach, Algorithm, Numerical Results, Notes) -- 4. S-CLONE (Approach, Algorithm, Numerical Results, Notes)- 5. Epilogue. –References En línea: http://dx.doi.org/10.1007/978-1-4614-4636-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32849 Ejemplares
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Título : Demand Flexibility in Supply Chain Planning Tipo de documento: documento electrónico Autores: Geunes, Joseph ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2012 Otro editor: Imprint: Springer Colección: SpringerBriefs in Optimization, ISSN 2190-8354 Número de páginas: XIII, 90 p Il.: online resource ISBN/ISSN/DL: 978-1-4419-9347-2 Idioma : Inglés (eng) Palabras clave: Mathematics Production management Mathematical optimization Operations research Management science Engineering economics economy Research, Science Economics, Organization, Logistics, Marketing Optimization Clasificación: 51 Matemáticas Resumen: This work encapsulates the essential developments in this field into a single resource, as well as to set an agenda for further development in the field. This brief focuses on the demand flexibility in supply chains with fragmented results distributed throughout the literature. These results have strong implications for managing real-world complex operations planning problems. This book exploits dimensions of demand flexibility in supply chains and characterizes the best fit between demand properties and operations capabilities and constraints. The origins and seminal works are traced in integrated demand and operations planning and an in-depth documentation is provided for the current state of the art. Systems with inherent costs and constraints that must respond to some set of demands at a minimum cost are examined. Crucial unanswered questions are explored and the high-value research directions are highlighted for both practice and for the development of new and interesting optimization models and algorithms Nota de contenido: 1. Scope of Problem Coverage and Introduction -- 2. Production and Inventory Planning Models with Demand Shaping -- 3. EOQ-Type Models with Demand Selection -- 4. Single-Period Stochastic Inventory Planning with Demand Selection -- 5. Dynamic Lot Sizing with Demand Selection and the Pricing Analog -- 6. Dynamic Lot Sizing with Market Selection -- 7. Assignment and Location Problems in Supply Chains -- 8. Branch and Price Decomposition for Assignment and Location Problems -- 9. Research Challenges in Supply Chain Planning with Flexible Demand En línea: http://dx.doi.org/10.1007/978-1-4419-9347-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32712 Demand Flexibility in Supply Chain Planning [documento electrónico] / Geunes, Joseph ; SpringerLink (Online service) . - New York, NY : Springer New York : Imprint: Springer, 2012 . - XIII, 90 p : online resource. - (SpringerBriefs in Optimization, ISSN 2190-8354) .
ISBN : 978-1-4419-9347-2
Idioma : Inglés (eng)
Palabras clave: Mathematics Production management Mathematical optimization Operations research Management science Engineering economics economy Research, Science Economics, Organization, Logistics, Marketing Optimization Clasificación: 51 Matemáticas Resumen: This work encapsulates the essential developments in this field into a single resource, as well as to set an agenda for further development in the field. This brief focuses on the demand flexibility in supply chains with fragmented results distributed throughout the literature. These results have strong implications for managing real-world complex operations planning problems. This book exploits dimensions of demand flexibility in supply chains and characterizes the best fit between demand properties and operations capabilities and constraints. The origins and seminal works are traced in integrated demand and operations planning and an in-depth documentation is provided for the current state of the art. Systems with inherent costs and constraints that must respond to some set of demands at a minimum cost are examined. Crucial unanswered questions are explored and the high-value research directions are highlighted for both practice and for the development of new and interesting optimization models and algorithms Nota de contenido: 1. Scope of Problem Coverage and Introduction -- 2. Production and Inventory Planning Models with Demand Shaping -- 3. EOQ-Type Models with Demand Selection -- 4. Single-Period Stochastic Inventory Planning with Demand Selection -- 5. Dynamic Lot Sizing with Demand Selection and the Pricing Analog -- 6. Dynamic Lot Sizing with Market Selection -- 7. Assignment and Location Problems in Supply Chains -- 8. Branch and Price Decomposition for Assignment and Location Problems -- 9. Research Challenges in Supply Chain Planning with Flexible Demand En línea: http://dx.doi.org/10.1007/978-1-4419-9347-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32712 Ejemplares
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Título : Group Testing Theory in Network Security : An Advanced Solution Tipo de documento: documento electrónico Autores: Thai, My T ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2012 Colección: SpringerBriefs in Optimization, ISSN 2190-8354 Número de páginas: XI, 86 p. 24 illus., 17 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-0128-5 Idioma : Inglés (eng) Palabras clave: Mathematics Computer communication systems Mathematical optimization Applied mathematics Engineering Industrial engineering Production Optimization Communication Networks and Appl.Mathematics/Computational Methods of Clasificación: 51 Matemáticas Resumen: Group Testing Theory in Network Security explores a new branch of group testing theory with an application which enhances research results in network security. This brief presents new solutions on several advanced network security problems and mathematical frameworks based on the group testing theory, specifically denial-of-service and jamming attacks. A new application of group testing, illustrated in this text, requires additional theories, such as size constraint group testing and connected group testing. Included in this text is a chapter devoted to discussing open problems and suggesting new solutions for various network security problems. This text also exemplifies the connection between mathematical approaches and practical applications to group testing theory in network security. This work will appeal to a multidisciplinary audience with interests in computer communication networks, optimization, and engineering En línea: http://dx.doi.org/10.1007/978-1-4614-0128-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32733 Group Testing Theory in Network Security : An Advanced Solution [documento electrónico] / Thai, My T ; SpringerLink (Online service) . - New York, NY : Springer New York, 2012 . - XI, 86 p. 24 illus., 17 illus. in color : online resource. - (SpringerBriefs in Optimization, ISSN 2190-8354) .
ISBN : 978-1-4614-0128-5
Idioma : Inglés (eng)
Palabras clave: Mathematics Computer communication systems Mathematical optimization Applied mathematics Engineering Industrial engineering Production Optimization Communication Networks and Appl.Mathematics/Computational Methods of Clasificación: 51 Matemáticas Resumen: Group Testing Theory in Network Security explores a new branch of group testing theory with an application which enhances research results in network security. This brief presents new solutions on several advanced network security problems and mathematical frameworks based on the group testing theory, specifically denial-of-service and jamming attacks. A new application of group testing, illustrated in this text, requires additional theories, such as size constraint group testing and connected group testing. Included in this text is a chapter devoted to discussing open problems and suggesting new solutions for various network security problems. This text also exemplifies the connection between mathematical approaches and practical applications to group testing theory in network security. This work will appeal to a multidisciplinary audience with interests in computer communication networks, optimization, and engineering En línea: http://dx.doi.org/10.1007/978-1-4614-0128-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32733 Ejemplares
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