The book presents a broad view on the nature of intelligent decision-making which is characterized by the use of models and methods in the framework of decision support for management. Contributions to this volume dedicated to Paul StAhly on the occasion of his 65th birthday include theoretical research and applications in optimization, operations research as well as decision support and management systems.

This edited book examines the challenges and opportunities arising from today's sharing economy from an operations management perspective. Individual chapter authors present state-of-the-art research that examines the general impact of sharing economy on production and consumption; the intermediary role of a sharing platform; crowdsourcing management; and context-based operational problems. Sharing economy refers to a market model that enables and facilitates the sharing of access to goods and services. For example, Uber allows riders to share a car. Airbnb allows homeowners to share their extra rooms with renters. Groupon crowdsources demands, enabling customers to share the benefit of discounted goods and services, whereas Kickstarter crowdsources funds, enabling backers to fund a project jointly. Unlike the classic supply chain settings in which a firm makes inventory and supply decisions, in sharing economy, supply is crowdsourced and can be modulated by a platform. The matching-supply-with-demand process in a sharing economy requires novel perspectives and tools to address challenges and identify opportunities. The book is comprised of 20 chapters that are divided into four parts. The first part explores the general impact of sharing economy on the production, consumption, and society. The second part explores the intermediary role of a sharing platform that matches crowdsourced supply with demand. The third part investigates the crowdsourcing management on a sharing platform, and the fourth part is dedicated to context-based operational problems of popular sharing economy applications. "While sharing economy is becoming omnipresence, the operations management (OM) research community has begun to explore and examine different business models in the transportation, healthcare, financial, accommodation, and sourcing sectors. This book presents a collection of the state-of-the-art research work conducted by a group of world-leading OM researchers in this area. Not only does this book cover a wide range of business models arising from the sharing economy, but it also showcases different modeling frameworks and research methods that cannot be missed. Ultimately, this book is a tour de force - informative and insightful!" Christopher S. Tang Distinguished Professor and Edward Carter Chair in Business Administration UCLA Anderson School of Management

This book provides theoretical and practical insights for effective decision making in situations that involve various types of conflict cleavages. Embedding historical analysis, negotiation analysis, political scientific analysis and game theoretical analysis in an integrated analytical framework allows a comprehensive perspective on various dilemmas and self-enforcing dynamics that inhibit decision making. The conceptualization of strategic facilitation highlights the value of leadership, chairmanship and the role of threshold states in facilitating decision making as the global climate change negotiations unfolds.

This handbook compiles state-of-the-art empirical studies and applications using Data Envelopment Analysis (DEA). It includes a collection of 18 chapters written by DEA experts. Chapter 1 examines the performance of CEOs of U.S. banks and thrifts. Chapter 2 describes the network operational structure of transportation organizations and the relative network data envelopment analysis model. Chapter 3 demonstrates how to use different types of DEA models to compute total-factor energy efficiency scores with an application to energy efficiency. In chapter 4, the authors explore the impact of incorporating customers' willingness to pay for service quality in benchmarking models on cost efficiency of distribution networks, and chapter 5 provides a brief review of previous applications of DEA to the professional baseball industry, followed by two detailed applications to Major League Baseball. Chapter 6 examines efficiency and productivity of U.S. property-liability (P-L) insurers using DEA, while chapter 7 presents a two-stage network DEA model that decomposes the overall efficiency of a decision-making unit into two components. Chapter 8 presents a review of the literature of DEA models for the perfoemance assessment of mutual funds, and chapter 9 discusses the management strategies formulation of the international tourist hotel industry in Taiwan. Chapter 10 presents a novel use of the two-stage network DEA to evaluate sustainable product design performances. In chapter 11 authors highlight limitations of some DEA environmental efficiency models, and chapter 12 reviews applications of DEA in secondary and tertiary education. Chapter 13 measures the relative performance of New York State school districts in the 2011-2012 academic year. Chapter 14 provides an introductory prelude to chapters 15 and 16, which both provide detailed applications of DEA in marketing. Chapter 17 then shows how to decompose a new total factor productivity index that satisfies all economically-relevant axioms from index theory with an application to U.S. agriculture. Finally, chapter 18 presents a unique study that conducts a DEA research front analysis, applying a network clustering method to group the DEA literature over the period 2000 to 2014.

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 I 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. Volume II 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.

This book is a comprehensive introduction of the reader into the simulation and modelling techniques and their application in the management of organisations. The book is rooted in the thorough understanding of systems theory applied to organisations and focuses on how this theory can apply to econometric models used in the management of organisations. The econometric models in this book employ linear and dynamic programming, graph theory, queuing theory, game theory, etc. and are presented and analysed in various fields of application, such as investment management, stock management, strategic decision making, management of production costs and the lifecycle costs of quality and non-quality products, production quality Management, etc.

This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.

This book provides readers with a timely and comprehensive yet concise view on the field of fuzzy logic and its real-world applications. The chapters, written by authoritative scholars in the field, report on promising new models for data analysis, decision making, and systems modeling, with a special emphasis on their applications in management science. The book is a token of appreciation from the fuzzy research community to Professor Christer Carlsson for his long time research and organizational commitment, which have among other things resulted in the foundation and success of the Institute for Advanced Management Systems Research (IAMSR) at Abo Akademi University, in Abo (Turku), Finland. The book serves as timely guide for the fuzzy logic and operations research communities alike.

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 papers based on the presentations and discussions at the international workshop on Big Data Smart Transportation Analytics held July 16 and 17, 2016 at Tongji University in Shanghai and chaired by Professors Ukkusuri and Yang. The book is intended to explore a multidisciplinary perspective to big data science in urban transportation, motivated by three critical observations: The rapid advances in the observability of assets, platforms for matching supply and demand, thereby allowing sharing networks previously unimaginable. The nearly universal agreement that data from multiple sources, such as cell phones, social media, taxis and transit systems can allow an understanding of infrastructure systems that is critically important to both quality of life and successful economic competition at the global, national, regional, and local levels. There is presently a lack of unifying principles and methodologies that approach big data urban systems. The workshop brought together varied perspectives from engineering, computational scientists, state and central government, social scientists, physicists, and network science experts to develop a unifying set of research challenges and methodologies that are likely to impact infrastructure systems with a particular focus on transportation issues. The book deals with the emerging topic of data science for cities, a central topic in the last five years that is expected to become critical in academia, industry, and the government in the future. There is currently limited literature for researchers to know the opportunities and state of the art in this emerging area, so this book fills a gap by synthesizing the state of the art from various scholars and help identify new research directions for further study.

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 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 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.

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 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.

Although several books or monographs on multiobjective optimization under uncertainty have been published, there seems to be no book which starts with an introductory chapter of linear programming and is designed to incorporate both fuzziness and randomness into multiobjective programming in a unified way. In this book, five major topics, linear programming, multiobjective programming, fuzzy programming, stochastic programming, and fuzzy stochastic programming, are presented in a comprehensive manner. Especially, the last four topics together comprise the main characteristics of this book, and special stress is placed on interactive decision making aspects of multiobjective programming for human-centered systems in most realistic situations under fuzziness and/or randomness.

Organization of each chapter is briefly summarized as follows: Chapter 2 is a concise and condensed description of the theory of linear programming and its algorithms. Chapter 3 discusses fundamental notions and methods of multiobjective linear programming and concludes with interactive multiobjective linear programming. In Chapter 4, starting with clear explanations of fuzzy linear programming and fuzzy multiobjective linear programming, interactive fuzzy multiobjective linear programming is presented. Chapter 5 gives detailed explanations of fundamental notions and methods of stochastic programming including two-stage programming and chance constrained programming. Chapter 6 develops several interactive fuzzy programming approaches to multiobjective stochastic programming problems. Applications to purchase and transportation planning for food retailing are considered in Chapter 7.

The book is self-contained because of the three appendices and answers to problems. Appendix A contains a brief summary of the topics from linear algebra. Pertinent results from nonlinear programming are summarized in Appendix B. Appendix C is a clear explanation of the Excel Solver, one of the easiest ways to solve optimization problems, through the use of simple examples of linear and nonlinear programming.

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.

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.

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

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.

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 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.

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.