Sergiy Butenko - Böcker

For students in industrial and systems engineering (ISE) and operations research (OR) to understand optimization at an advanced level, they must first grasp the analysis of algorithms, computational complexity, and other concepts and modern developments in numerical methods. Satisfying this prerequisite, Numerical Methods and Optimization: An Introduction combines the materials from introductory numerical methods and introductory optimization courses into a single text. This classroom-tested approach enriches a standard numerical methods syllabus with optional chapters on numerical optimization and provides a valuable numerical methods background for students taking an introductory OR or optimization course.The first part of the text introduces the necessary mathematical background, the digital representation of numbers, and different types of errors associated with numerical methods. The second part explains how to solve typical problems using numerical methods. Focusing on optimization methods, the final part presents basic theory and algorithms for linear and nonlinear optimization.The book assumes minimal prior knowledge of the topics. Taking a rigorous yet accessible approach to the material, it includes some mathematical proofs as samples of rigorous analysis but in most cases, uses only examples to illustrate the concepts. While the authors provide a MATLAB® guide and code available for download, the book can be used with other software packages.

A co-operative system is a collection of dynamical objects, which communicate and co-operate in order to achieve a common or shared objective. The co-operation of entities is achieved through communication; either explicitly by message passing, or implicitly via observation of another entities' state. As in natural systems, cooperation may assume a hierarchical form and the control processes may be distributed or decentralized. Due to the dynamic nature of individuals and the interaction between them, the problems associated with co-operative systems typically involve many uncertainties. Moreover, in many cases co-operative systems are required to operate in a noisy or hazardous environment, which creates special challenges for designing the control process. Considerable progress has been observed in all aspects regarding the study of co-operative systems including modeling of co-operative systems, resource allocation, discrete event driven dynamical control, continuous and hybrid dynamical control, and theory of the interaction of information, control, and hierarchy.Solution methods have been proposed using control and optimization approaches, emergent rule based techniques, game theoretic and team theoretic approaches. Measures of performance have been suggested that include the effects of hierarchies and information structures on solutions, performance bounds, concepts of convergence and stability, and problem complexity. These and other topics were discusses at the Second Annual Conference on Cooperative Control and Optimization in Gainesville, Florida. Refereed papers written by selected conference participants from the conference are gathered in this volume, which presents problem models; theoretical results; and algorithms for various aspects of co-operative control.

Over the past several years, cooperative control and optimization has un­ questionably been established as one of the most important areas of research in the military sciences. Even so, cooperative control and optimization tran­ scends the military in its scope -having become quite relevant to a broad class of systems with many exciting, commercial, applications. One reason for all the excitement is that research has been so incredibly diverse -spanning many scientific and engineering disciplines. This latest volume in the Cooperative Systems book series clearly illustrates this trend towards diversity and creative thought. And no wonder, cooperative systems are among the hardest systems control science has endeavored to study, hence creative approaches to model­ ing, analysis, and synthesis are a must! The definition of cooperation itself is a slippery issue. As you will see in this and previous volumes, cooperation has been cast into many different roles and therefore has assumed many diverse meanings. Perhaps the most we can say which unites these disparate concepts is that cooperation (1) requires more than one entity, (2) the entities must have some dynamic behavior that influences the decision space, (3) the entities share at least one common objective, and (4) entities are able to share information about themselves and their environment. Optimization and control have long been active fields of research in engi­ neering.

During the last decades, considerable progress has been observed in all aspects regarding the study of cooperative systems including modeling of cooperative systems, resource allocation, discrete event driven dynamical control, continuous and hybrid dynamical control, and theory of the interaction of information, control, and hierarchy. Solution methods have been proposed using control and optimization approaches, emergent rule based techniques, game theoretic and team theoretic approaches. Measures of performance have been suggested that include the effects of hierarchies and information structures on solutions, performance bounds, concepts of convergence and stability, and problem complexity. These and other topics were discusses at the Second Annual Conference on Cooperative Control and Optimization in Gainesville, Florida. Refereed papers written by selected conference participants from the conference are gathered in this volume, which presents problem models, theoretical results, and algorithms for various aspects of cooperative control. Audience: The book is addressed to faculty, graduate students, and researchers in optimization and control, computer sciences and engineering.

Over the past several years, cooperative control and optimization has un­ questionably been established as one of the most important areas of research in the military sciences. Even so, cooperative control and optimization tran­ scends the military in its scope -having become quite relevant to a broad class of systems with many exciting, commercial, applications. One reason for all the excitement is that research has been so incredibly diverse -spanning many scientific and engineering disciplines. This latest volume in the Cooperative Systems book series clearly illustrates this trend towards diversity and creative thought. And no wonder, cooperative systems are among the hardest systems control science has endeavored to study, hence creative approaches to model­ ing, analysis, and synthesis are a must! The definition of cooperation itself is a slippery issue. As you will see in this and previous volumes, cooperation has been cast into many different roles and therefore has assumed many diverse meanings. Perhaps the most we can say which unites these disparate concepts is that cooperation (1) requires more than one entity, (2) the entities must have some dynamic behavior that influences the decision space, (3) the entities share at least one common objective, and (4) entities are able to share information about themselves and their environment. Optimization and control have long been active fields of research in engi­ neering.

For students in industrial and systems engineering (ISE) and operations research (OR) to understand optimization at an advanced level, they must first grasp the analysis of algorithms, computational complexity, and other concepts and modern developments in numerical methods. Satisfying this prerequisite, Numerical Methods and Optimization: An Introduction combines the materials from introductory numerical methods and introductory optimization courses into a single text. This classroom-tested approach enriches a standard numerical methods syllabus with optional chapters on numerical optimization and provides a valuable numerical methods background for students taking an introductory OR or optimization course.The first part of the text introduces the necessary mathematical background, the digital representation of numbers, and different types of errors associated with numerical methods. The second part explains how to solve typical problems using numerical methods. Focusing on optimization methods, the final part presents basic theory and algorithms for linear and nonlinear optimization.The book assumes minimal prior knowledge of the topics. Taking a rigorous yet accessible approach to the material, it includes some mathematical proofs as samples of rigorous analysis but in most cases, uses only examples to illustrate the concepts. While the authors provide a MATLAB® guide and code available for download, the book can be used with other software packages.

Optimization in Science and Engineering is dedicated in honor of the 60th birthday of Distinguished Professor Panos M. Pardalos. Pardalos’s past and ongoing work has made a significant impact on several theoretical and applied areas in modern optimization. As tribute to the diversity of Dr. Pardalos’s work in Optimization, this book comprises a collection of contributions from experts in various fields of this rich and diverse area of science.Topics highlight recent developments and include:Deterministic global optimizationVariational inequalities and equilibrium problemsApproximation and complexity in numerical optimizationNon-smooth optimization Statistical models and data miningApplications of optimization in medicine, energy systems, and complex network analysisThis volume will be of great interest to graduate students, researchers, and practitioners, in the fields of optimization and engineering.

Optimization in Science and Engineering is dedicated in honor of the 60th birthday of Distinguished Professor Panos M. Pardalos. Pardalos’s past and ongoing work has made a significant impact on several theoretical and applied areas in modern optimization. As tribute to the diversity of Dr. Pardalos’s work in Optimization, this book comprises a collection of contributions from experts in various fields of this rich and diverse area of science.Topics highlight recent developments and include:Deterministic global optimizationVariational inequalities and equilibrium problemsApproximation and complexity in numerical optimizationNon-smooth optimization Statistical models and data miningApplications of optimization in medicine, energy systems, and complex network analysisThis volume will be of great interest to graduate students, researchers, and practitioners, in the fields of optimization and engineering.

This volume constitutes the proceedings of the 12th International Conference on Algorithmic Aspects in Information and Management, AAIM 2018, held in Dallas, Texas, USA, in December 2018.The 25 full papers presented were carefully reviewed and selected. The papers deal with current trends of research on algorithms, data structures, operation research, combinatorial optimization and their applications.

Researchers and practitioners in computer science, optimization, operations research and mathematics will find this book useful as it illustrates optimization models and solution methods in discrete, non-differentiable, stochastic, and nonlinear optimization.

Researchers and practitioners in computer science, optimization, operations research and mathematics will find this book useful as it illustrates optimization models and solution methods in discrete, non-differentiable, stochastic, and nonlinear optimization.

This book presents the up-to-date research developments in economics, management and optimization applied to sports, which would be of interest to researchers and practitioners in sports industry, and could be used as supplementary reading in related courses and seminars. In particular, the volume contains research papers and reviews addressing the following issues: methods for ranking teams and evaluating players' performance; techniques for predicting outcomes of sport competitions; economics for professional leagues; optimal strategies in sports; optimal referee assignment techniques; scheduling and managing sport tournaments. The specific sports discussed in the book include American football, soccer, baseball, cricket, basketball, track and field, and hockey.

This book presents the up-to-date research developments in economics, management and optimization applied to sports, which would be of interest to researchers and practitioners in sports industry, and could be used as supplementary reading in related courses and seminars. In particular, the volume contains research papers and reviews addressing the following issues: methods for ranking teams and evaluating players' performance; techniques for predicting outcomes of sport competitions; economics for professional leagues; optimal strategies in sports; optimal referee assignment techniques; scheduling and managing sport tournaments. The specific sports discussed in the book include American football, soccer, baseball, cricket, basketball, track and field, and hockey.

During the last century, we have witnessed the birth and evolution of sport as an economic activity, which has created jobs on the one hand, but also problems of management on the other. This process has not been immune from the parti- lar characteristics associated with sport, typically united here more than in other activities: technique, physical effort, entertainment and passion. And all this within a framework of ever-increasing consumption of ?nancial resources. It is not s- prising, therefore, that commonly-used economic models, based on mechanistic approaches, do not provide a viable solution to increasingly complex and incre- ingly frequent problems. Any attempt to apply such an approach in this technical, economic and ?nancial context can only result in failure. The high degree of subj- tivity inherent in sporting activity requires new tools, in which remodeled conc- tual, theoretical and technical elements should play an important role. Complexity, uncertainty and subjectivity are therefore basic to understand, and deal with, the phenomenon of sport. The necessity of resorting to these elements was identi?ed over a quarter of a century ago by a small group of professors and researchers at the University of Barcelona. Together we started the ?rst postgraduate courses and organized se- nars to alert sports centre managers, as well as to make private and public organi- tions aware of the increasing importance of a proper, speci?c management for sports organizations.

During the last century, we have witnessed the birth and evolution of sport as an economic activity, which has created jobs on the one hand, but also problems of management on the other. This process has not been immune from the parti- lar characteristics associated with sport, typically united here more than in other activities: technique, physical effort, entertainment and passion. And all this within a framework of ever-increasing consumption of ?nancial resources. It is not s- prising, therefore, that commonly-used economic models, based on mechanistic approaches, do not provide a viable solution to increasingly complex and incre- ingly frequent problems. Any attempt to apply such an approach in this technical, economic and ?nancial context can only result in failure. The high degree of subj- tivity inherent in sporting activity requires new tools, in which remodeled conc- tual, theoretical and technical elements should play an important role. Complexity, uncertainty and subjectivity are therefore basic to understand, and deal with, the phenomenon of sport. The necessity of resorting to these elements was identi?ed over a quarter of a century ago by a small group of professors and researchers at the University of Barcelona. Together we started the ?rst postgraduate courses and organized se- nars to alert sports centre managers, as well as to make private and public organi- tions aware of the increasing importance of a proper, speci?c management for sports organizations.