This book presents a variety of advanced research papers in optimization and dynamics written by internationally recognized researchers in these fields. As an example of applying optimization in sport, it introduces a new method for finding the optimal bat sizes in baseball and softball. The book is divided into three parts: operations research, dynamics, and applications. The operations research section deals with the convergence of Newton-type iterations for solving nonlinear equations and optimum problems, the limiting properties of the Nash bargaining solution, the utilization of public goods, and optimizing lot sizes in the automobile industry. The topics in dynamics include special linear approximations of nonlinear systems, the dynamic behavior of industrial clusters, adaptive learning in oligopolies, periodicity in duopolies resulting from production constraints, and dynamic models of love affairs. The third part presents applications in the fields of reverse logistic network design for end-of-life wind turbines, fuzzy optimization of the structure of agricultural products, water resources management in the restoration plans for a lake and also in groundwater supplies. In addition it discusses applications in reliability engineering to find the optimal preventive replacement times of deteriorating equipment and using bargaining theory to determine the best maintenance contract. The diversity of the application areas clearly illustrates the usefulness of the theory and methodology of optimization and dynamics in solving practical problems.

"Focusing on turning an initial idea into a project with a successful outcome, this book fills a gap in current literature on project management and is thoroughly grounded in the latest research in this field. It emphasizes the practical application of decision making based on qualitative and judgmental information"--

Multiple Criteria Decision Making and its Applications to Economic Problems ties Multiple Criteria Decision Making (MCDM)/Multiple Objective Optimization (MO) and economics together. It describes how MCDM methods (goal programming) can be used in economics.

The volume consists of two parts. Part One of the book introduces the MCDM approaches. This first part, comprising Chapters 1-5, is basically an overview of MCDM methods that can most likely be used to address a wide range of economic problems. Readers looking for an in-depth discussion of multi-criteria analysis can grasp and become acquainted with the initial MCDM tools, language and definitions.

Part Two, which comprises Chapters 6-8, focuses on the theoretical core of the book. Thus in Chapter 6 an economic meaning is given to several key concepts on MCDM, such as ideal point, distance function, etc. It illustrates how Compromise Programming (CP) can support the standard premise of utility optimisation in economics as well as how it is capable of approximating the standard utility optimum when the decision-makers' preferences are incompletely specified. Chapter 7 deals entirely with production analysis. The main characteristic throughout the Chapter refers to a standard joint production scenario, analysed from the point of view of MCDM schemes. Chapter 8 focuses on the utility specification problem in the n-arguments space within a risk aversion context. A link between Arrows' risk aversion coefficient and CP utility permits this task.

The book is intended for postgraduate students and researchers in economics with an OR/MS orientation or in OR/MS with an economic orientation. In short, it attempts to fruitfully link economics and MCDM.

Strategic management deals with a very broad set of questions, issues, and problems associated with general management. This book introduces research carried out in several frontier areas of strategic management: Strategy, Information Systems, R&D/Engineering, Marketing, Ethics, Governance, Issues Management and New Ventures.
Especially noteworthy is its major emphasis on extending the purview and scope of strategic management by the integration of established and emerging functional areas into the mainstream of the strategic management process. The scope of areas covered ranges from the corporate to public sector, and from corporate to new ventures. Academics and practitioners interested in the ramifications of latest developments in the theory and practice of strategic management will find this book of interest.

In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed."

This book presents recent work in the physics and economics of management through the developmental theory and practice of management science/operations research (MS/OR) that goes beyond the author s earlier book on the same subject. (Volume 125 in Springer s MS/OR series) This current work makes a useful contribution to the next-generation discrete system of science and management for a better society.

The scope of the book is focused on the science and management of the 3M&I Time system in the discrete world, where that system is a complex class consisting of humans, material/machine, money and time. The system is treated by a stochastic/intelligence (medium) approach. The science of this system is the interdisciplinary science of physics, management, economics and related fields and is based on synthesis and intelligence in the new discrete world. Here, this domain is referred to as a discrete and complex science (of physics and economics) in industry and society.

Another domain, which is referred to as higher management science and operations in this book, stems from the change in traditional management to higher management driven by the power of information and communications technology (ICT) in the cloud computing/global age. This domain exists to meet the needs of logic for real-time/systematic decisions and management in a changeable, speeded-up, and risk environment."

Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. The resulting entropy optimization models have proved their usefulness with successful applications in areas such as image reconstruction, pattern recognition, statistical inference, queuing theory, spectral analysis, statistical mechanics, transportation planning, urban and regional planning, input-output analysis, portfolio investment, information analysis, and linear and nonlinear programming. While entropy optimization has been used in different fields, a good number of applicable solution methods have been loosely constructed without sufficient mathematical treatment. A systematic presentation with proper mathematical treatment of this material is needed by practitioners and researchers alike in all application areas. The purpose of this book is to meet this need. Entropy Optimization and Mathematical Programming offers perspectives that meet the needs of diverse user communities so that the users can apply entropy optimization techniques with complete comfort and ease. With this consideration, the authors focus on the entropy optimization problems in finite dimensional Euclidean space such that only some basic familiarity with optimization is required of the reader.

This handbook for the Methodology of Societal Complexity describes the theoretical development of the field and lays the foundation for the application of the Compram Methodology in the context of addressing complex societal problems. As such, it offers a valuable resource for scientists, practitioners, politicians, master and PhD students in the fields of methodology, the social sciences, operational research, management and political science and for all others who are professionally involved in handling complex societal problems. These problems are the kind that fill the front page of quality newspapers; they have a huge impact on society, involve a variety of phenomena and actors, and are therefore difficult to handle. The structured Compram Methodology provides sound guidelines for handling real-life societal problems democratically, sustainably and transparently. Examples of the use of the Compram Methodology are provided in the domain of global safety with regard to healthcare, economics, climate change, terrorism, large city problems, large technological projects and floods.

Complex societal problems must be treated as multi-disciplinary, multi-actor, multi-level and often as multi-continental issues. As such, they call for a multi-disciplinary and multi-actor approach that takes into account the emotional aspects of the problem and the problem handling process, including the micro, meso and macro level, which can be accomplished using the methods, models and tools from the field of the Methodology of Societal Complexity.

The Compram Methodology improves the problem handling process and increases the quality of interventions and therefore the quality of life. Handling complex societal problems can reduce conflicts, save money and ultimately even save lives.

Dorien J. DeTombe is an internationally recognized expert and founder of the theory of the Methodology of Societal Complexity and the Compram Methodology.

This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set. It can also be regarded as a stand-alone volume presenting chapters dealing with various aspects of the subject in a self-contained way.

This book presents an analysis of the dynamics and the complexity of new product development projects which are organized according to the concept of concurrent engineering. The approach of the authors includes both a theoretical and an empirical treatment of the topic, based on the theory of design structure matrices. Readers will discover diverse perspectives and mathematical models, as well as an extensive discussion of two case studies.

This book showcases a large variety of multiple criteria decision applications (MCDAs), presenting them in a coherent framework provided by the methodology chapters and the comments accompanying each case study. The chapters describing MCDAs invite the reader to experiment with MCDA methods and perhaps develop new variants using data from these case studies or other cases they encounter, equipping them with a broader perception of real-world problems and how to overcome them with the help of MCDAs.

This book discusses emerging themes in the area of humanitarian logistics. It examines how humanitarian logistics and supply chains play a key role, focusing on rapidly delivering the correct amount of goods, people and monetary resources to the locations needed to achieve the success of relief efforts in response to global emergencies such as flood, earthquakes, wars etc. With an increase in the frequency, magnitude and impact of both natural and manmade disasters, effective delivery of humanitarian aid is an issue that is becoming increasingly important in the context of disaster management. The book focuses on how logistics systems and supply chains responsible for delivering this aid from origin to recipients can be made more effective and efficient. It also discusses how the development of information technology systems that can provide visibility to the disaster relief supply chain marks a huge step forward for the humanitarian sector as a whole. As more organizations begin to adopt and implement these systems and visibility is established, the use of key performance indicators will then become essential to further enhance the efficiency and effectiveness of these supply chains.

The objective of the book is to give a selection from the papers, which summarize several important results obtained within the framework of the Jozsef Hatvany Doctoral School operating at the University of Miskolc, Hungary. In accordance with the three main research areas of the Doctoral School established for Information Science, Engineering and Technology, the papers can be classified into three groups. They are as follows: (1) Applied Computational Science; (2) Production Information Engineering (IT for Manufacturing included); (3) Material Stream Systems and IT for Logistics. As regards the first area, some papers deal with special issues of algorithms theory and its applications, with computing algorithms for engineering tasks, as well as certain issues of data base systems and knowledge intensive systems. Related to the second research area, the focus is on Production Information Engineering with special regard to discrete production processes. In the second research area the papers show some new integrated systems suitable for optimizing discrete production processes in a top-down way. The papers connecting with the third research field deal with different issues of materials stream systems and logistics, taking into consideration of applied mathematical models and IT-tools. The book makes an effort to ensure certain equilibrium between theory and practice and to show some new approach both from theoretical modelling aspect, as well as experimental and practical point of view.

This book is an extension of the author's first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN). It walks the learner through the steps of fitting and solving fifty BBN numerically, using mathematical proof. The author wrote this book primarily for inexperienced learners as well as professionals, while maintaining a proof-based academic rigor. The author's first book on this topic, a primer introducing learners to the basic complexities and nuances associated with learning Bayes' theorem and inverse probability for the first time, was meant for non-statisticians unfamiliar with the theorem-as is this book. This new book expands upon that approach and is meant to be a prescriptive guide for building BBN and executive decision-making for students and professionals; intended so that decision-makers can invest their time and start using this inductive reasoning principle in their decision-making processes. It highlights the utility of an algorithm that served as the basis for the first book, and includes fifty 2-, 3-, and 4-event BBN of numerous variants.

The main contents and character of the monograph did not change with respect to the first edition. However, within most chapters we incorporated quite a number of modifications which take into account the recent development of the field, the very valuable suggestions and comments that we received from numerous colleagues and students as well as our own experience while using the book. Some errors and misprints in the first edition are also corrected. Reiner Horst May 1992 Hoang Tuy PREFACE TO THE FIRST EDITION The enormous practical need for solving global optimization problems coupled with a rapidly advancing computer technology has allowed one to consider problems which a few years aga would have been considered computationally intractable. As a consequence, we are seeing the creation of a large and increasing number of diverse algorithms for solving a wide variety of multiextremal global optimization problems. The goal of this book is to systematically clarify and unify these diverse approaches in order to provide insight into the underlying concepts and their pro perties. Aside from a coherent view of the field much new material is presented."

The volume is dedicated to Stephen Smale on the occasion of his 80th birthday.Besides his startling 1960 result of the proof of the Poincare conjecture for all dimensionsgreater than or equal to five, Smale's ground breaking contributions invarious fields in Mathematics have marked the second part of the 20th century andbeyond. Stephen Smale has done pioneering work in differential topology, globalanalysis, dynamical systems, nonlinear functional analysis, numerical analysis, theoryof computation and machine learning as well as applications in the physical andbiological sciences and economics. In sum, Stephen Smale has manifestly brokenthe barriers among the different fields of mathematics and dispelled some remainingprejudices. He is indeed a universal mathematician. Smale has been honoredwith several prizes and honorary degrees including, among others, the Fields Medal(1966), The Veblen Prize (1966), the National Medal of Science (1996) and theWolfPrize (2006/2007)."

For first courses in operations research, operations management. Covers a broad range of optimization techniques, including linear programming, network flows, integer/combinational optimization, and nonlinear programming. Emphasizes the importance of modeling and problem formulation, this text teaches students how to apply algorithms to real-world problems to arrive at optimal solutions. Visit the author-maintained web site athttp: //comp.uark.edu/ rrardin/oorboo

The field of discrete event systems has emerged to provide a formal treatment of many of the man-made systems such as manufacturing systems, communication networks, automated traffic systems, database management systems, and computer systems that are event-driven, highly complex, and not amenable to the classical treatments based on differential or difference equations. Discrete event systems is a growing field that utilizes many interesting mathematical models and techniques. In Modeling and Control of Logical Discrete Event Systems, the focus is on a high level treatment of discrete event systems, where the order of events, rather their occurrence times, is the principal concern. Such treatment is needed to guarantee that the system under study meets desired logical goals. In this framework, discrete event systems are modeled by formal languages or, equivalently, by state machines. The field of logical discrete event systems is an interdisciplinary field -- it includes ideas from computer science, control theory, and operations research. Our goal is to bring together in one book the relevant techniques from these fields. Modeling and Control of Logical Discrete Event Systems is the first book of this kind for professionals in the area of discrete event systems. The book is also designed for a graduate level course on logical discrete event systems. It contains all the necessary background material in formal language theory and lattice theory. The only prerequisite is some degree of mathematical maturity'. Several examples and exercise problems are included in each chapter to facilitate classroom teaching.

Equilibrium is a concept used in operations research and economics to understand the interplay of factors and problems arising from competitive systems in the economic world. The problems in this area are large and complex and have involved a variety of mathematical methodologies. In this monograph, the authors have widened the scope of theoretical work with a new approach, projected dynamical systems theory', to previous work in variational inequality theory. While most classical work in this area is static, the introduction to the theory of projected dynamical systems will allow many real-life dynamic situations and problems to be handled and modeled. This monograph includes: a new theoretical approach, projected dynamical system', which allows the researcher to model real-life situations more accurately; new mathematical methods allowing researchers to combine other theoretical approaches with the projected dynamical systems approach; a framework in which research can adequately model natural, financial and human (real life) situations in competitive equilibrium problems; the computational and numerical methods for the implementation of the methods and theory discussed in the book; stability analysis, algorithms and computational procedures are offered for each set of applications.

Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of the 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 research being conducted by members of the INFORMS Computing Society.

This tutorial introduces readers to several variants of routing problems with profits. In these routing problems each node has a certain profit, and not all nodes need to be visited. Since the orienteering problem (OP) is by far the most frequently studied problem in this category of routing problems, the book mainly focuses on the OP. In turn, other problems are presented as variants of the OP, focusing on the similarities and differences. The goal of the OP is to determine a subset of nodes to visit and in which order, so that the total collected profit is maximized and a given time budget is not exceeded.The book provides a comprehensive review of variants of the OP, such as the team OP, the team OP with time windows, the profitable tour problem, and the prize-collecting travelling salesperson problem. In addition, it presents mathematical models and techniques for solving these OP variants and discusses their complexity. Several simple examples and benchmark instances, together with their best-known results, are also included. Finally, the book reviews the latest applications of these problems in the fields of logistics, tourism and others.

This book focuses on the emergence of the "science of sustainability" and the key concepts in making sustainability operational in an organization. The authors discuss the methods, techniques and tools needed to manage the impact of sustainability and how these can be reformulated into business models and solutions for new growth and applications. They then move onto the reformulation of future thinking processes before ending by looking towards an approach for the measurement of sustainability and competitiveness.

International Applications of Productivity and Efficiency Analysis features a complete range of techniques utilized in frontier analysis, including extensions of existing techniques and the development of new techniques. Another feature is that most of the contributions use panel data in a variety of approaches. Finally, the range of empirical applications is at least as great as the range of techniques, and many of the applications are of considerable policy relevance.

At the end of the nineteenth century Lyapunov and Poincare developed the so called qualitative theory of differential equations and introduced geometric- topological considerations which have led to the concept of dynamical systems. In its present abstract form this concept goes back to G.D. Birkhoff. This is also the starting point of Chapter 1 of this book in which uncontrolled and controlled time-continuous and time-discrete systems are investigated. Controlled dynamical systems could be considered as dynamical systems in the strong sense, if the controls were incorporated into the state space. We, however, adapt the conventional treatment of controlled systems as in control theory. We are mainly interested in the question of controllability of dynamical systems into equilibrium states. In the non-autonomous time-discrete case we also consider the problem of stabilization. We conclude with chaotic behavior of autonomous time discrete systems and actual real-world applications.