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.

Risk analysis is crucial in stochastic supply chain models. Over the past few years, the pace has quickened for research attempting to explore risk analysis issues in supply chain management problems, while the majority of recent papers focus on conceptual framework or computational numerical analysis. Pioneered by Nobel laureate Markowitz in the 1950s, the mean-risk (MR) formulation became a fundamental theory for risk management in finance. Despite the significance and popularity of MR-related approaches in finance, their applications in studying multi-echelon supply chain management problems have only been seriously explored in recent years. While the MR approach has already been shown to be useful in conducting risk analysis in stochastic supply chain models, there is no comprehensive reference source that provides the state-of-the-art findings on this important model for supply chain management. Thus it is significant to have a book that reviews and extends the MR related works for supply chain risk analysis. This book is organized into five chapters. Chapter 1 introduces the topic, offers a timely review of various related areas, and explains why the MR approach is important for conducting supply chain risk analysis. Chapter 2 examines the single period inventory model with the mean-variance and mean-semi-deviation approaches. Extensive discussions on the efficient frontiers are also reported. Chapter 3 explores the infinite horizon multi-period inventory model with a mean-variance approach. Chapter 4 investigates the supply chain coordination problem with a versatile target sales rebate contract and a risk averse retailer possessing the mean-variance optimization objective. Chapter 5 concludes the book and discusses various promising future research directions and extensions. Every chapter can be taken as a self-contained article, and the notation within each chapter is consistently employed.

There is one major factor that explains business actions that has thus far escaped thorough exploration. That factor is clout, or as it is more broadly understood, power. Those with clout in the business organizations make the decisions and influence what the business does. Yet the origins and uses of clout are hidden. Everyone wants to know more about this inner world as clout is still largely unrecognized in studies of corporate culture. With Clout, the first researched-based book on the topic, Bolland fills this void. He systematically analyses the subject and answers the many questions about this aspect of business life, including exploring what organization clout is, how it has evolved, how it is manifested, how it is used and how it relates to other aspects of business organizations. Readers will be able to apply findings to their own career, and students will gain a tested framework for understanding the importance of this subject.

This book discusses how to build optimization tools able to generate better future studies. It aims at showing how these tools can be used to develop an adaptive learning environment that can be used for decision making in the presence of uncertainties. The book starts with existing fuzzy techniques and multicriteria decision making approaches and shows how to combine them in more effective tools to model future events and take therefore better decisions. The first part of the book is dedicated to the theories behind fuzzy optimization and fuzzy cognitive map, while the second part presents new approaches developed by the authors with their practical application to trend impact analysis, scenario planning and strategic formulation. The book is aimed at two groups of readers, interested in linking the future studies with artificial intelligence. The first group includes social scientists seeking for improved methods for strategic prospective. The second group includes computer scientists and engineers seeking for new applications and current developments of Soft Computing methods for forecasting in social science, but not limited to this.

This handbook represents a milestone in the progression of Data Envelopment Analysis (DEA). Written by experts who are often major contributors to DEA theory, it includes a collection of chapters that represent the current state-of-the-art in DEA research. Topics include distance functions and their value duals, cross-efficiency measures in DEA, integer DEA, weight restrictions and production trade-offs, facet analysis in DEA, scale elasticity, benchmarking and context-dependent DEA, fuzzy DEA, non-homogenous units, partial input-output relations, super efficiency, treatment of undesirable measures, translation invariance, stochastic nonparametric envelopment of data, and global frontier index. Focusing only on new models/approaches of DEA, the book includes contributions from Juan Aparicio, Mette Asmild, Yao Chen, Wade D. Cook, Juan Du, Rolf Fare, Julie Harrison, Raha Imanirad, Andrew Johnson, Chiang Kao, Abolfazl Keshvari, Timo Kuosmanen, Sungmook Lim, Wenbin Liu, Dimitri Margaritis, Reza Kazemi Matin, Ole B. Olesen, Jesus T. Pastor, Niels Chr. Petersen, Victor V. Podinovski, Paul Rouse, Antti Saastamoinen, Biresh K. Sahoo, Kaoru Tone, and Zhongbao Zhou.

The development of Operations Research (OR) requires constant improvements, such as the integration of research results with business applications and innovative educational practice. The full deployment and commercial exploitation of goods and services generally need the construction of strong synergies between educational institutions and businesses. The IO2015 -XVII Congress of APDIO aims at strengthening the knowledge triangle in education, research and innovation, in order to maximize the contribution of OR for sustainable growth, the promoting of a knowledge-based economy, and the smart use of finite resources. The IO2015-XVII Congress of APDIO is a privileged meeting point for the promotion and dissemination of OR and related disciplines, through the exchange of ideas among teachers, researchers, students , and professionals with different background, but all sharing a common desire that is the development of OR.

This book introduces a novel approach to discrete optimization, providing both theoretical insights and algorithmic developments that lead to improvements over state-of-the-art technology. The authors present chapters on the use of decision diagrams for combinatorial optimization and constraint programming, with attention to general-purpose solution methods as well as problem-specific techniques. The book will be useful for researchers and practitioners in discrete optimization and constraint programming. "Decision Diagrams for Optimization is one of the most exciting developments emerging from constraint programming in recent years. This book is a compelling summary of existing results in this space and a must-read for optimizers around the world." [Pascal Van Hentenryck]

This book promotes and describes the application of objective and effective decision making in asset management based on mathematical models and practical techniques that can be easily implemented in organizations. This comprehensive and timely publication will be an essential reference source, building on available literature in the field of asset management while laying the groundwork for further research breakthroughs in this field. The text provides the resources necessary for managers, technology developers, scientists and engineers to adopt and implement better decision making based on models and techniques that contribute to recognizing risks and uncertainties and, in general terms, to the important role of asset management to increase competitiveness in organizations.

Location analysis has matured from an area of theoretical inquiry that was designed to explain observed phenomena to a vibrant field which can be and has been used to locate items as diverse as landfills, fast food outlets, gas stations, as well as politicians and products in issue and feature spaces. Modern location science is dealt with by a diverse group of researchers and practitioners in geography, economics, operations research, industrial engineering, and computer science. Given the tremendous advances location science has seen from its humble beginnings, it is time to look back. The contributions in this volume were written by eminent experts in the field, each surveying the original contributions that created the field, and then providing an up-to-date review of the latest contributions. Specific areas that are covered in this volume include: * The three main fields of inquiry: minisum and minimax problems and covering models * Nonstandard location models, including those with competitive components, models that locate undesirable facilities, models with probabilistic features, and problems that allow interactions between facilities * Descriptions and detailed examinations of exact techniques including the famed Weiszfeld method, and heuristic methods ranging from Lagrangean techniques to Greedy algorithms * A look at the spheres of influence that the facilities generate and that attract customers to them, a topic crucial in planning retail facilities * The theory of central places, which, other than in mathematical games, where location science was born

This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the fundamentals, covers the classical topics (paths, flows, matching, matroids, NP-completeness, approximation algorithms) in detail, and proceeds to advanced and recent topics, some of which have not appeared in a textbook before. Throughout, it contains complete but concise proofs, and also provides numerous exercises and references. This sixth edition has again been updated, revised, and significantly extended. Among other additions, there are new sections on shallow-light trees, submodular function maximization, smoothed analysis of the knapsack problem, the (ln 4+e)-approximation for Steiner trees, and the VPN theorem. Thus, this book continues to represent the state of the art of combinatorial optimization.

When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.

Semidefinite and conic optimization is a major and thriving research area within the optimization community. Although semidefinite optimization has been studied (under different names) since at least the 1940s, its importance grew immensely during the 1990s after polynomial-time interior-point methods for linear optimization were extended to solve semidefinite optimization problems.

Since the beginning of the 21st century, not only has research into semidefinite and conic optimization continued unabated, but also a fruitful interaction has developed with algebraic geometry through the close connections between semidefinite matrices and polynomial optimization. This has brought about important new results and led to an even higher level of research activity.

This "Handbook on Semidefinite, Conic and Polynomial Optimization "provides the reader with a snapshot of the state-of-the-art in the growing and mutually enriching areas of semidefinite optimization, conic optimization, and polynomial optimization. It contains a compendium of the recent research activity that has taken place in these thrilling areas, and will appeal to doctoral" "students, young graduates, and experienced researchers alike.

The Handbook's thirty-one chapters are organized into four parts: "Theory," covering significant theoretical developments as well as the interactions between conic optimization and polynomial optimization;"Algorithms," documenting the directions of current algorithmic development;"Software," providing an overview of the state-of-the-art;"Applications," dealing with the application areas where semidefinite and conic optimization has made a significant impact in recent years.

This volume discusses the latest techniques and their economic applications for modern industries like computer, pharmaceutical, banking and other manaufacturing. These industries are most important for a growing economy. Both econometric and mathematical programming techniques are analyzed so as to develop a synthetic approach. The industrial applications not only emphasize the various aspects of R&D spending, advertisement expenditure and imperfect market structures, but also assess the economic benefits of measuring some specific performance paremers in the light of policy reforms adopted in a growing economy.

Growing transportation costs and tight delivery schedules mean that good located decisions are more crucial than ever in the success or failure of industrial and puplic projects. The development of realistic location models is an essential phase in every locational decision process. Especially when dealing with geometric representations of continuous (planar) location model problems, the goegraphical reality must be incorporated. This text develops the mathematical implications of barriers to the geometrical and analytical characteristics of continuous location problems. Besides their relevance in the application of location theoretic results, location problems with barriers are also very interesting from a mathematical point of view. The nonconvexity of distance measures in the presence of barriers leads to nonconvex optimization problems. Most of the classical methods in continuous location theory rely heaily on the convexity of the objective function and will thus fail in this context. On the other hand, general methods in global optimization capable of treating nonconvex problems ignore the geometric charateristics of the location problems considered. Theoretic as well as algorithmic approaches are utilized to overcome the described difficulties for the solution of location problems with barriers. Depending on the barrier shapes, the underlying distance measure, and type of objective function, different concepts are conceived to handle the nonconvexity of the problem. This book will appeal to those working in operations research and management science and mathematicians interested in optimization theory and its applications.

To derive rational and convincible solutions to practical decision making problems in complex and hierarchical human organizations, the decision making problems are formulated as relevant mathematical programming problems which are solved by developing optimization techniques so as to exploit characteristics or structural features of the formulated problems. In particular, for resolving con?ict in decision making in hierarchical managerial or public organizations, the multi level formula tion of the mathematical programming problems has been often employed together with the solution concept of Stackelberg equilibrium. However, weconceivethatapairoftheconventionalformulationandthesolution concept is not always suf?cient to cope with a large variety of decision making situations in actual hierarchical organizations. The following issues should be taken into consideration in expression and formulation of decision making problems. Informulationofmathematicalprogrammingproblems, itistacitlysupposedthat decisions are made by a single person while game theory deals with economic be havior of multiple decision makers with fully rational judgment. Because two level mathematical programming problems are interpreted as static Stackelberg games, multi level mathematical programming is relevant to noncooperative game theory; in conventional multi level mathematical programming models employing the so lution concept of Stackelberg equilibrium, it is assumed that there is no communi cation among decision makers, or they do not make any binding agreement even if there exists such communication. However, for decision making problems in such as decentralized large ?rms with divisional independence, it is quite natural to sup pose that there exists communication and some cooperative relationship among the decision maker

This book provides a self-contained review of all the relevant topics in probability theory. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Carolina at Chapel Hill.

This book is a collection of representative and novel works done in Data Mining, Knowledge Discovery, Clustering and Classification that were originally presented in French at the EGC'2013 (Toulouse, France, January 2013) and EGC'2014 Conferences (Rennes, France, January 2014). These conferences were respectively the 13th and 14th editions of this event, which takes place each year and which is now successful and well-known in the French-speaking community. This community was structured in 2003 by the foundation of the French-speaking EGC society (EGC in French stands for "Extraction et Gestion des Connaissances" and means "Knowledge Discovery and Management", or KDM). This book is aiming at all researchers interested in these fields, including PhD or MSc students, and researchers from public or private laboratories. It concerns both theoretical and practical aspects of KDM. The book is structured in two parts called "Applications of KDM to real datasets" and "Foundations of KDM".

This book studies storage policies in warehousing systems and maintenance-support strategies for critical operational systems in warehouses, which are the most important issues affecting operational efficiency of warehousing systems. It expands on the theory of class-based storage by considering a finite number of items in store, and also introduces the maintenance-support strategy founded on performance-based contract theory. It is a valuable resource for researchers, practitioners and engineers in the fields of industrial engineering, operations management, operations research and management science.

Based on the 2005 publication The Financial Appraisal Profile Model , this book discusses how the FAP model can present an integrated process for the appraisal of financial and strategic benefits and the assessment of risk in ICT (Information Communication Technology) project proposals.

This is a sequel to the book by Dr. A. Ashimov and his colleagues, Macroeconomic Analysis and Economic Policy Based on Parametric Control. The authors have expanded both the developed mathematical apparatus and the scope of problems and applications stemming from the practice of steering a national economy of a small country in the dynamic environment of the international economic order. The developed theoretical foundation is used in Chapter 1 to suggest a decision support system operating in the framework of state economic policy making. Chapter 2 presents various mathematical models built on the basis of the available statistical data and provides quality assessment of these models. Parametric control problems are being formulated on the basis of these models as problems of mathematical programming, and the obtained solutions are subjected to analyses and interpretations. This is demonstrated by the analysis of the effect of uncontrollable factors on the problem solutions. Chapter 3 is aimed at the modelling and analysis of cyclic phenomena in economics and their structural stability. Chapter 4 presents solutions of specific problems of national economy and analysis and interpretation of their solutions. In summary, the authors formulate comprehensive mathematical models of some critical mechanisms in micro economics previously known only on a qualitative level. They provide vigorous mathematical analysis of the models that justifies their applicability for the formulation of parametric control problems, and the existence of model-based solutions. The complexity of the resultant problems is addressed by the formulation of the appropriate algorithms. The described methodology leads to the development of computer-based decision support systems.

Practical Goal Programming is intended to allow academics and practitioners to be able to build effective goal programming models, to detail the current state of the art, and to lay the foundation for its future development and continued application to new and varied fields. Suitable as both a text and reference, its nine chapters first provide a brief history, fundamental definitions, and underlying philosophies, and then detail the goal programming variants and define them algebraically. Chapter 3 details the step-by-step formulation of the basic goal programming model, and Chapter 4 explores more advanced modeling issues and highlights some recently proposed extensions.

Chapter 5 then details the solution methodologies of goal programming, concentrating on computerized solution by the Excel Solver and LINGO packages for each of the three main variants, and includes a discussion of the viability of the use of specialized goal programming packages. Chapter 6 discusses the linkages between Pareto Efficiency and goal programming. Chapters 3 to 6 are supported by a set of ten exercises, and an Excel spreadsheet giving the basic solution of each example is available at an accompanying website.

Chapter 7 details the current state of the art in terms of the integration of goal programming with other techniques, and the text concludes with two case studies which were chosen to demonstrate the application of goal programming in practice and to illustrate the principles developed in Chapters 1 to 7. Chapter 8 details an application in healthcare, and Chapter 9 describes applications in portfolio selection.

Improving Risk Analysis shows how to better assess and manage uncertain risks when the consequences of alternative actions are in doubt. The constructive methods of causal analysis and risk modeling presented in this monograph will enable to better understand uncertain risks and decide how to manage them. The book is divided into three parts. Parts 1 shows how high-quality risk analysis can improve the clarity and effectiveness of individual, community, and enterprise decisions when the consequences of different choices are uncertain. Part 2 discusses social decisions. Part 3 illustrates these methods and models, showing how to apply them to health effects of particulate air pollution. "Tony Cox's new book addresses what risk analysts and policy makers most need to know: How to find out what causes what, and how to quantify the practical differences that changes in risk management practices would make. The constructive methods in Improving Risk Analysis will be invaluable in helping practitioners to deliver more useful insights to inform high-stakes decisions and policy,in areas ranging from disaster planning to counter-terrorism investments to enterprise risk management to air pollution abatement policies. Better risk management is possible and practicable; Improving Risk Analysis explains how." Elisabeth Pate-Cornell, Stanford University "Improving Risk Analysis offers crucial advice for moving policy-relevant risk analyses towards more defensible, causally-based methods. Tony Cox draws on his extensive experience to offer sound advice and insights that will be invaluable to both policy makers and analysts in strengthening the foundations for important risk analyses. This much-needed book should be required reading for policy makers and policy analysts confronting uncertain risks and seeking more trustworthy risk analyses." Seth Guikema, Johns Hopkins University "Tony Cox has been a trail blazer in quantitative risk analysis, and his new book gives readers the knowledge and tools needed to cut through the complexity and advocacy inherent in risk analysis. Cox's careful exposition is detailed and thorough, yet accessible to non-technical readers interested in understanding uncertain risks and the outcomes associated with different mitigation actions. Improving Risk Analysis should be required reading for public officials responsible for making policy decisions about how best to protect public health and safety in an uncertain world." Susan E. Dudley, George Washington University

Column Generation is an insightful overview of the state-of-the-art in integer programming column generation and its many applications. The volume begins with "A Primer in Column Generation" which outlines the theory and ideas necessary to solve large-scale practical problems, illustrated with a variety of examples. Other chapters follow this introduction on "Shortest Path Problems with Resource Constraints," "Vehicle Routing Problem with Time Window," "Branch-and-Price Heuristics," "Cutting Stock Problems," each dealing with methodological aspects of the field. Three chapters deal with transportation applications: "Large-scale Models in the Airline Industry," "Robust Inventory Ship Routing by Column Generation," and "Ship Scheduling with Recurring Visits and Visit Separation Requirements." Production is the focus of another three chapters: "Combining Column Generation and Lagrangian Relaxation," "Dantzig-Wolfe Decomposition for Job Shop Scheduling," and "Applying Column Generation to Machine Scheduling." The final chapter by FranAois Vanderbeck, "Implementing Mixed Integer Column Generation," reviews how to set-up the Dantzig-Wolfe reformulation, adapt standard MIP techniques to the column generation context (branching, preprocessing, primal heuristics), and deal with specific column generation issues (initialization, stabilization, column management strategies).

The book is the first systematic treatment of column generation methodologies. It will provide students, researchers, and experienced column generation users with a much-needed state-of-the-art survey of the field.

This textbook presents the basics of game theory both on an undergraduate level and on a more advanced mathematical level. It is the second, revised version of the successful 2008 edition. The book covers most topics of interest in game theory, including cooperative game theory. Part I presents introductions to all these topics on a basic yet formally precise level. It includes chapters on repeated games, social choice theory, and selected topics such as bargaining theory, exchange economies, and matching. Part II goes deeper into noncooperative theory and treats the theory of zerosum games, refinements of Nash equilibrium in strategic as well as extensive form games, and evolutionary games. Part III covers basic concepts in the theory of transferable utility games, such as core and balancedness, Shapley value and variations, and nucleolus. Some mathematical tools on duality and convexity are collected in Part IV. Every chapter in the book contains a problem section. Hints, answers and solutions are included.

Social capital as a concept, is a comparatively recent addition to the regional economic and innovation literature. Facets of social capital are generally acknowledged to include trust, collaboration, cooperation, bridging and bonding social network ties, and reciprocity. Nevertheless, forms of social capital such as bonding and bridging social capital, are less frequently explored in the literature. Innovation and Social Capital in Organizational Ecosystems breaks down the concept of innovation into its main components, which represent a spectrum of innovation activity from technology-based innovation to hidden and social innovation, in order to support executives concerned with innovation and social capital in different work communities and environments. Highlighting a range of topics including regional development, social innovation, network capital, and more, this book is ideally designed for researchers, professionals, students, policymakers, and practitioners.