Fuzzy Control of Queuing Systems
21 detailed case studies demonstrate an efficient departure from classical techniques. Unique work creating a new Research and Development topic. Multidisciplinary approach that will benefit researchers and students throughout the fields of artificial intelligence, operations research, optimal control, Internet techniques, communications and traffic control industries. Equipped with an extensive bibliography for easy reference and scope for further study.
Finance for Engineers : Evaluation and Funding of Capital Projects
Finance for Engineers: Evaluation and Funding of Capital Projects provides a framework for engineers and scientists to undertake financial evaluations and assessments of engineering or production projects. The material covered enables the reader to understand how the economics of a technical project affects the finances of the company. The integration of the technical and financial decision-making is demonstrated through case studies and examples relevant to the practising engineer.
Fading Foundations : Probability and the Regress Problem
This book addresses the age-old problem of infinite regresses in epistemology. How can we ever come to know something if knowing requires having good reasons, and reasons can only be good if they are backed by good reasons in turn? The problem has puzzled philosophers ever since antiquity, giving rise to what is often called Agrippa's Trilemma. The current volume approaches the old problem in a provocative and thoroughly contemporary way. Taking seriously the idea that good reasons are typically probabilistic in character, it develops and defends a new solution that challenges venerable philosophical intuitions and explains why they were mistakenly held. Key to the new solution is the phenomenon of fading foundations, according to which distant reasons are less important than those that are nearby.
Factorization of Matrix and Operator Functions : The State Space Method
The present book deals with factorization problems for matrix and operator functions. The problems originate from, or are motivated by, the theory of non-selfadjoint operators, the theory of matrix polynomials, mathematical systems and control theory, the theory of Riccati equations, inversion of convolution operators, theory of job scheduling in operations research. The book systematically employs a geometric principle of factorization which has its origins in the state space theory of linear input-output systems and in the theory of characteristic operator functions. This principle allows one to deal with different factorizations from one point of view. Covered are canonical factorization, minimal and non-minimal factorizations, pseudo-canonical factorization, and various types of degree one factorization.
Extending the Horizons : Advances in Computing, Optimization, and Decision Technologies
Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state-of-the-art in the interface between OR/MS and CS/AI and of the high caliber of research being conducted by members of the INFORMS Computing Society.
Evolutionary Scheduling
Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.
Enterprise Risk Management Models
Offers a comprehensive guide to several aspects of risk, including information systems, disaster management, supply chain and disaster management perspectives. A major portion of the book is devoted to presenting a number of operations research models that have been (or could be) applied to enterprise supply risk management, especially from the supply chain perspective.
Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics ; International Workshop, SLS 2007, Brussels, Belgium, September 6-8, 2007, Proceedings
Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. However, in recent years it has become evident that at the core of this development task there is a highly complex engineering process, which combines various aspects of algorithm design with empirical analysis techniques and problem-specific background, and which relies heavily on knowledge from a number of disciplines and areas, including computer science, operations research, artificial intelligence, and statistics. This development process needs to be - sisted by a sound methodology that addresses the issues arising in the various phases of algorithm design, implementation, tuning, and experimental eval- tion.
Dynamics in Logistics : Twenty-Five Years of Interdisciplinary Logistics Research in Bremen, Germany
Highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization.
Discrete-Time Markov Chains : Two-Time-Scale Methods and Applications
The motivation stems from existing and emerging applications in optimization and control of complex hybrid Markovian systems in manufacturing, wireless communication, and financial engineering. Much effort in this book is devoted to designing system models arising from these applications, analyzing them via analytic and probabilistic techniques, and developing feasible computational algorithms so as to reduce the inherent complexity. This book presents results including asymptotic expansions of probability vectors, structural properties of occupation measures, exponential bounds, aggregation and decomposition and associated limit processes, and interface of discrete-time and continuous-time systems. One of the salient features is that it contains a diverse range of applications on filtering, estimation, control, optimization, and Markov decision processes, and financial engineering.
Discrete Optimization with Interval Data : Minmax Regret and Fuzzy Approach
This book is a valuable source of information for all operations research practitioners who are interested in modern approaches to problem solving. Apart from the description of the theoretical framework, it also presents some algorithms that can be applied to solve problems that arise in practice.
Design of advanced manufacturing systems : Models for capacity planning in advanced manufacturing systems
The aim of this book is to provide a framework and speci?c methods and tools for the selection and con?guration of capacity of Advanced Manufacturing Systems (AMS). In particular this book de?nes an - chitecture where the multidisciplinary aspects of the designofAMSare properly organized and addressed. The tool will support the decisi- maker in the de?nition of the con?guration of the system which is best suited for the particular competitive context where the ?rm operates or wants tooperate. Thisbookisofinterest for academic researchers in the ?eldofind- trial engineering and particularly indicated in the areas of operations and manufacturing strategy.
Decomposition Techniques in Mathematical Programming : Engineering and Science Applications
This textbook for students and practitioners presents a practical approach to decomposition techniques in optimization. It provides an appropriate blend of theoretical background and practical applications in engineering and science, which makes the book interesting for practitioners, as well as engineering, operations research and applied economics graduate and postgraduate students. "Decomposition Techniques in Mathematical Programming" is based on clarifying, illustrative and computational examples and applications from electrical, mechanical, energy and civil engineering as well as applied mathematics and economics. It addresses decomposition in linear programming, mixed-integer linear programming, nonlinear programming, and mixed-integer nonlinear programming, and provides rigorous decomposition algorithms as well as heuristic ones.
Decision Procedures : An Algorithmic Point of View
Concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research.
Decision Modeling and Behavior in Complex and Uncertain Environments
Devoted to examining new research at the interface of operations research, behavioral and cognitive sciences, and decision analysis. In these 14 self-contained chapters, four themes emerge, providing the reader with a variety of perspectives both theoretic and applied to meet the challenges of devising models to understand the decision-making process. The main broad topics include: the integration of decision analysis and behavioral models / innovations in behavioral models / exploring descriptive behavior models / experimental studies
Decision Making under Deep Uncertainty : From Theory to Practice
Focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them.
Data analytics, computational statistics, and operations research for engineers : Methodologies and applications
Presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information.
Data Analysis and Decision Support
Presents advances in data analysis and decision support and gives an actual overview on the interface between mathematics, operations research, statistics, computer science, and management science. Areas that receive considerable attention in the book are discrimination and clustering, multidimensional scaling, data mining and more.
Cooperative systems : Control and optimization
This book provides an insight in the basic understanding of cooperative systems as well as in theory, modeling, and applications of cooperative control, optimization and related problems.
Cooperative stochastic differential games
Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises.



















