This is a new edition of Kleijnen's advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Altogether, this new edition has approximately 50% new material not in the original book. More specifically, the author has made significant changes to the book's organization, including placing the chapter on Screening Designs immediately after the chapters on Classic Designs, and reversing the order of the chapters on Simulation Optimization and Kriging Metamodels. The latter two chapters reflect how active the research has been in these areas. The validation section has been moved into the chapter on Classic Assumptions versus Simulation Practice, and the chapter on Screening now has a section on selecting the number of replications in sequential bifurcation through Wald's sequential probability ration test, as well as a section on sequential bifurcation for multiple types of simulation responses. Whereas all references in the original edition were placed at the end of the book, in this edition references are placed at the end of each chapter. From Reviews of the First Edition: "Jack Kleijnen has once again produced a cutting-edge approach to the design and analysis of simulation experiments." (William E. BILES, JASA, June 2009, Vol. 104, No. 486)

This book offers a timely overview of fuzzy and rough set theories and methods. Based on selected contributions presented at the International Symposium on Fuzzy and Rough Sets, ISFUROS 2017, held in Varadero, Cuba, on October 24-26, 2017, the book also covers related approaches, such as hybrid rough-fuzzy sets and hybrid fuzzy-rough sets and granular computing, as well as a number of applications, from big data analytics, to business intelligence, security, robotics, logistics, wireless sensor networks and many more. It is intended as a source of inspiration for PhD students and researchers in the field, fostering not only new ideas but also collaboration between young researchers and institutions and established ones.

The Handbook of Mathematical Economics aims to provide a definitive source, reference, and teaching supplement for the field of mathematical economics. It surveys, as of the late 1970's the state of the art of mathematical economics. This is a constantly developing field and all authors were invited to review and to appraise the current status and recent developments in their presentations. In addition to its use as a reference, it is intended that this Handbook will assist researchers and students working in one branch of mathematical economics to become acquainted with other branches of this field. Volume 1 deals with "Mathematical Methods in Economics," including reviews of the concepts and techniques that have been most useful for the mathematical development of economic theory.

For more information on the Handbooks in Economics series, please see our home page on http: //www.elsevier.nl/locate/hes

This book introduces a new paradigm called 'Optimization in Changeable Spaces' (OCS) as a useful tool for decision making and problem solving. It illustrates how OCS incorporates, searches, and constructively restructures the parameters, tangible and intangible, involved in the process of decision making. The book elaborates on OCS problems that can be modeled and solved effectively by using the concepts of competence set analysis, Habitual Domain (HD) and the mental operators called the 7-8-9 principles of deep knowledge of HD. In addition, new concepts of covering and discovering processes are proposed and formulated as mathematical tools to solve OCS problems. The book also includes reformulations of a number of illustrative real-life challenging problems that cannot be solved by traditional optimization techniques into OCS problems, and details how they can be addressed. Beyond that, it also includes perspectives related to innovation dynamics, management, artificial intelligence, artificial and e-economics, scientific discovery and knowledge extraction. This book will be of interest to managers of businesses and institutions, policy makers, and educators and students of decision making and behavior in DBA and/or MBA.

This book shows how transit assignment models can be used to describe and predict the patterns of network patronage in public transport systems. It provides a fundamental technical tool that can be employed in the process of designing, implementing and evaluating measures and/or policies to improve the current state of transport systems within given financial, technical and social constraints. The book offers a unique methodological contribution to the field of transit assignment because, moving beyond "traditional" models, it describes more evolved variants that can reproduce:* intermodal networks with high- and low-frequency services;* realistic behavioural hypotheses underpinning route choice;* time dependency in frequency-based models; and* assumptions about the knowledge that users have of network conditionsthat are consistent with the present and future level of information that intelligent transport systems (ITS) can provide. The book also considers the practical perspective of practitioners and public transport operators who need to model and manage transit systems; for example, the role of ITS is explained with regard to their potential in data collection for modelling purposes and validation techniques, as well as with regard to the additional data on network patronage and passengers' preferences that influences the network-management and control strategies implemented. In addition, it explains how the different aspects of network operations can be incorporated in traditional models and identifies the advantages and disadvantages of doing so. Lastly, the book provides practical information on state-of-the-art implementations of the different models and the commercial packages that are currently available for transit modelling. Showcasing original work done under the aegis of the COST Action TU1004 (TransITS), the book provides a broad readership, ranging from Master and PhD students to researchers and from policy makers to practitioners, with a comprehensive tool for understanding transit assignment models.

Theory and application of a variety of mathematical techniques in economics are presented in this volume. Topics discussed include: martingale methods, stochastic processes, optimal stopping, the modeling of uncertainty using a Wiener process, Ito's Lemma as a tool of stochastic calculus, and basic facts about stochastic differential equations. The notion of stochastic ability and the methods of stochastic control are discussed, and their use in economic theory and finance is illustrated with numerous applications.
The applications covered include: futures, pricing, job search, stochastic capital theory, stochastic economic growth, the rational expectations hypothesis, a stochastic macroeconomic model, competitive firm under price uncertainty, the Black-Scholes option pricing theory, optimum consumption and portfolio rules, demand for index bonds, term structure of interest rates, the market risk adjustment in project valuation, demand for cash balances and an asset pricing model.

The Handbook of Mathematical Economics aims to provide a definitive source, reference, and teaching supplement for the field of mathematical economics. It surveys, as of the late 1970's the state of the art of mathematical economics. This is a constantly developing field and all authors were invited to review and to appraise the current status and recent developments in their presentations. In addition to its use as a reference, it is intended that this Handbook will assist researchers and students working in one branch of mathematical economics to become acquainted with other branches of this field. Volume 2 elaborates on "Mathematical Approaches to Microeconomic Theory," including consumer, producer, oligopoly, and duality theory, as well as "Mathematical Approaches to Competitive Equilibrium" including such aspects of competitive equilibrium as existence, stability, uncertainty, the computation of equilibrium prices, and the core of an economy.

For more information on the Handbooks in Economics series, please see our home page on http: //www.elsevier.nl/locate/hes

Safe and high-efficiency operation are two main issues in rail transportation. This book focuses on these two key issues, bringing together a wealth of research to offer theoretical and technical support for rail operations and maintenance. In addition, it presents a comprehensive active safety assurance system for rail transportation, which includes the quantitative state identification and prediction of train components; rail transportation safety and reliability assessment methods; and rail transportation risk assessment at the rail networks level, which achieves the quantitative and high-precision monitoring of complex systems in real-time. In addition, it extends active safety based theory to safety prognostic analysis in the traffic system. Lastly, representative case studies verify that the theory is suitable for the actual traffic system.

This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.

This monograph aims to familiarize readers with the problem of evaluating the quality and reliability of digital geographic information in terms of their use. It identifies the key requirements for the functionality of this information and describes the system of evaluating its quality and reliability. The whole text is supplemented by examples that document the impact of different quality of the information on the entire decision-making process in command and control systems at the rescue and military levels. The monograph is primarily intended for professionals who are responsible for the implementation of digital geographic information in command and control systems, or for those who use them in their work. For this reason, particular attention is paid especially to the user aspects of the digital geographic information used. Vaclav Talhofer is Full Professor of Cartography and Geoinformatics at the University of Defense in Brno, Czech Republic. Sarka Hoskova-Mayerova is Associate Professor of Mathematics at the University of Defense in Brno, Czech Republic. Alois Hofmann is a teacher and scientist of Cartography and Geoinformatics at the University of Defense in Brno, Czech Republic. All authors contributing to this book have been extensively studying the methods and procedures for the use of digital geographic information, especially in the environment of the Czech Armed Forces.

This book focuses on the use of quantitative methods for both business and management, helping readers understand the most relevant quantitative methods for managerial decision-making. Pursuing a highly practical approach, the book reduces the theoretical information to a minimum, so as to give full prominence to the analysis of real business problems. Each chapter includes a brief theoretical explanation, followed by a real-life managerial case that needs to be solved, which is accompanied by a corresponding Microsoft Excel (R) dataset. The practical cases and exercises are solved using Excel, and for each problem, the authors provide an Excel file with the complete solution and corresponding calculations, which can be downloaded easily from the book's website. Further, in an appendix, readers can find solutions to the same problems, but using the R statistical language. The book represents a valuable reference guide for postgraduate, MBA and executive education students, as it offers a hands-on, practical approach to learning quantitative methods in a managerial context. It will also be of interest to managers looking for a practical and straightforward way to learn about quantitative methods and improve their decision-making processes.

This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems. The book's twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja-Bretones-Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes. Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot's stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem. The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few.

This book, companion to Foundations of Location Analysis (Springer, 2011), highlights some of the applications of location analysis within the spheres of businesses, those that deal with public services and applications that deal with law enforcement and first responders. While the Foundations book reviewed the theory and first contributions, this book describes how different location techniques have been used to solve real problems. Since many real problems comprise multiple objectives, in this book there is more presence of tools from multicriteria decision making and multiple-objective optimization. The section on business applications looks at such problems as locating bank branches, the potential location of a logistics park, sustainable forest management and layout problems in a hospital, a much more difficult type of problem than mere location problems. The section on public services presents chapters on the design of habitats for wildlife, control of forest fires, the location of intelligent sensors along highways for timely emergency response, locating breast cancer screening centers, an economic analysis for the locations of post offices and school location. The final section of the book includes chapters on the well-known problem of locating fire stations, a model for the location of sensors for travel time information, the problem of police districting, locations of jails, location of Coast Guard vessels and finally, a survey of military applications of location analysis throughout different periods of recent history.

Collected together in this book are ten state-of-the-art expository articles on the most important topics in optimization, written by leading experts in the field. The book therefore provides a primary reference for those performing research in some area of optimization or for those who have some basic knowledge of optimization techniques but wish to learn the most up-to-date and efficient algorithms for particular classes of problems. The first sections of each chapter are expository and therefore accessible to master's level graduate students. However, the chapters also contain advanced material on current topics of interest to researchers. For instance there are chapters which describe the polynomial-time linear programming algorithms of Khachian and Karmarkar and the techniques used to solve combinatorial and integer programming problems, an order of magnitude larger than was possible just a few years ago. Overall a comprehensive yet lively and up-to-date discussion of the state-of-the-art in optimization is presented in this book.

This research contributes to the growing body of knowledge as well as offers significant theoretical contributions and policy implications. As far as the researcher's knowledge, this is the first research of its type that investigates the relationship between digital enabled transformation of government and citizens' trust & confidence in government. The proposed conceptual model also makes a novel contribution at a conceptual level, which can be used as a frame of reference by researchers as well as practitioners when planning ICT-enabled transformation projects in government. The context of the research is the Kingdom of Bahrain, the top-ranked country in ICT adoption in the Gulf Cooperation Council (GCC) region.

This book provides an overview of the concept of economic psychology from behavioral and mathematical perspectives and related theoretical and empirical findings. Economic psychology is defined briefly as a general term for descriptive theories to explain the psychological processes of microeconomic behaviors and macroeconomic phenomena. However, the psychological methodology and knowledge of economic psychology have also been applied widely in such fields as economics, business administration, and engineering, and they are expected to become increasingly useful in the future-a trend suggested in several eminent scholars' studies. The book explains the numerous behavioral and mathematical models of economic psychology related to micro- and macroeconomic phenomena that have been proposed in the past, and introduces new models that are useful to explain human economic behaviors. It concludes with speculations about the future of modern economic psychology, referring to its connection with fields related to neuroscience, such as neuroeconomics, which have been developed in recent years. Readers require no advanced expertise; nonetheless, an introductory understanding of psychology, business administration, and economics, and a high- school-graduate level of mathematics are useful. To aid readers, each chapter includes a bibliography, which can be referred for more details related to economic psychology.

In scheduling theory, the models that have attracted considerable attention during the last two decades allow the processing times to be variable, i.e., to be subjected to various effects that make the actual processing time of a job dependent on its location in a schedule. The impact of these effects includes, but is not limited to, deterioration and learning. Under the first type of effect, the later a job is scheduled, the longer its actual processing time becomes. In the case of learning, delaying a job will result in shorter processing times. Scheduling with Time-Changing Effects and Rate-Modifying Activities covers and advances the state-of-the-art research in this area. The book focuses on single machine and parallel machine scheduling problems to minimize either the maximum completion time or the sum of completion times of all jobs, provided that the processing times are subject to various effects. Models that describe deterioration, learning and general non-monotone effects to be considered include positional, start-time dependent, cumulative and their combinations, which cover most of the traditionally used models. The authors also consider more enhanced models in which the decision-maker may insert certain Rate-Modifying Activities (RMA) on processing machines, such as for example, maintenance or rest periods. In any case, the processing times of jobs are not only dependent on effects mentioned above but also on the place of a job in a schedule relative to an RMA. For most of the enhanced models described in the book, polynomial-time algorithms are presented which are based on similar algorithmic ideas such as reduction to linear assignment problems (in a full form or in a reduced form), discrete convexity, and controlled generation of options.

The scope of this book is Operations Research methods in Agriculture and a thorough discussion of derived applications in the Agri-food industry. The book summarizes current research and practice in this area and illustrates the development of useful approaches to deal with actual problems arising in the agriculture sector and the agri-food industry. This book is intended to collect in one volume high quality chapters on Methods and Applications in Agriculture and Agri-food industry considering both theoretical issues and application results. Methods applied to problems in agriculture and the agri-food industry include, but are not restricted to, the following themes: Dynamic programming Multi-criteria decision methods Markov decision processes Linear programming Stochastic programming Parameter estimation and knowledge acquisition Learning from data Simulation Descriptive and normative decision tree techniques, including: agent modelling and simulation, and state of the art surveys Each chapter includes some standard and traditional methodology but also some recent research advances. All the applications presented in the chapters have been inspired and motivated by the demands from the agriculture and food production areas.

In Industry 4.0, industrial productions are adjusted to complete smart automation, which means introducing self-automation methods, self-configuration, self-diagnosis of problems and removal, cognition, and intelligent decision making. This implementation of Industry 4.0 brings about a change in business paradigms and production models, and this will be reflected at all levels of the production process including supply chains and will involve all workers in the production process from managers to cyber-physical systems designers and customers as end-users. The Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing is an essential reference source that explores the development and integration of Industry 4.0 by examining changes and innovations to manufacturing processes as well as its applications in different industrial areas. Featuring coverage on a wide range of topics such as cyber physical systems, integration criteria, and artificial intelligence, this book is ideally designed for mechanical engineers, electrical engineers, manufacturers, supply chain managers, logistics specialists, investors, managers, policymakers, production scientists, researchers, academicians, and students at the postgraduate level.

The theme of this book is the self-generation of information by the self-modification of systems. The author explains why biological and cognitive processes exhibit identity changes in the mathematical and logical sense. This concept is the basis of a new organizational principle which utilizes shifts of the internal semantic relations in systems. There are mathematical discussions of various classes of systems (Turing machines, input-output systems, synergetic systems, non-linear dynamics etc), which are contrasted with the author's new principle. The most important implications of this include a new conception on the nature of information and which also provides a new and coherent conceptual view of a wide class of natural systems. This book merits the attention of all philosophers and scientists concerned with the way we create reality in our mathematical representations of the world and the connection those representations have with the way things really are.

This textbook presents a coherent and robust structure for integrated risk management in the context of operations and finance. It explains how the operations-finance interface jointly optimizes material and financial flows under intricate risk exposures. The book covers financial flexibility, operational hedging, enterprise risk management (ERM), supply chain risk management (SCRM), integrated risk management (IRM), supply chain finance (SCF), and financial management of supply chain strategies. Both qualitative and quantitative approaches - including conceptualization, theory building, analytical modeling, and empirical research - are used to assess the value creation by integrating operations and finance. "This book provides a comprehensive description of the interactions between finance and operations and of how managers can best make decisions in recognition of these effects." John R. Birge, University of Chicago"Supply chain finance is an emerging area where innovations can unlock great values to complement the advances in information and physical flows of supply chain." Hau L. Lee, Stanford University"This book provides an excellent overview of supply chain finance and its most recent advances." Jan A. Van Mieghem, Northwestern University"This book is indispensable for advanced students as well as practitioners when looking for a pedagogical sound and scientific rigorous approach to Supply Chain Finance." Ralf W. Seifert, IMD/EPFL"The book advances our knowledge on the interface between operations and finance and provides managerial guidelines for effective risk management in the supply chain." Xiande Zhao, CEIBS

This monograph provides a detailed analysis on fair queueing rules from a normative, a strategic, and a non-cooperative viewpoint. The queueing problem is concerned with the following situation: There is a group of agents who must be served in a facility. The facility can handle only one agent at a time and agents incur waiting costs. The problem is to find the order in which to serve agents and monetary transfers they should receive. The queueing problem has been studied extensively in the recent literature.

A service economy era is coming As the basic discipline of service dominant era, service science mainly studies common rules of service activities, aiming to provide theoretical bases for creating service value in the new era. The book, which integrates knowledge of service management, operational management, logistics and supply chain management, constructs a research system for this emerging discipline. Service science research system constitutes service philosophy, resource allocation, operational management and service technology. Many cases about China s service enterprises are incorporated in the book, in the hope of providing readers an insight into not only service science but also the development of China s service economy."

The "Handbook of Simulation Optimization" presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes.

This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.

Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes's analysis of uncertainty. There is a need for further generalization - a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than computations over numbers and probabilities.

The monograph exposes the foundations of a new decision theory with imperfect decision-relevant information on environment and a decision maker's behavior. This theory is based on the synthesis of the fuzzy sets theory with perception-based information and the probability theory.

The book is self containing and represents in a systematic way the decision theory with imperfect information into the educational systems. The book will be helpful for teachers and students of universities and colleges, for managers and specialists from various fields of business and economics, production and social sphere.

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