The Second Edition of this book presents the state of the art in this important field. Marketing decision models constitute a core component of the marketing discipline and the area is changing rapidly, not only due to fundamental advances in methodology and model building, but also because of the recent developments in information technology, the Internet and social media. This Handbook contains eighteen chapters that cover the most recent developments of marketing decision models in different domains of marketing. Compared to the previous edition, thirteen chapters are entirely new, while the remaining chapters represent complete updates and extensions of the previous edition. This new edition of the Handbook has chapters on models for substantive marketing problems, such as customer relationship management, customer loyalty management, website design, Internet advertising, social media, and social networks. In addition, it contains chapters on recent methodological developments that are gaining popularity in the area of marketing decision models, such as structural modeling, learning dynamics, choice modeling, eye-tracking and measurement. The introductory chapter discusses the main developments of the last decade and discusses perspectives for future developments.

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.

The proceedings focus on selected aspects of the current and upcoming trends in transportation, logistics and decision-making. In detail the included scientific papers analyze the problem of Decision Making under Uncertainty, Stochastic Optimization, Transportation, Logistics and Intelligent Business. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of the symposium "The Sixth International Forum on Decision Sciences", which took place in Jinan, Shandong province, China.

From the Preface: This festschrift is devoted to recognize the career of a man who not only witnessed the growth of operations research from its inception, but also contributed significantly to this growth. Dr. Salah E. Elmaghraby received his doctorate degree from Cornell University in 1958, and since then, his scholarly contributions have enriched the fields of production planning and scheduling and project scheduling. This collection of papers is contributed in his honor by his students, colleagues, and acquaintances. It offers a tribute to the inspiration received from his work, and from his guidance and advice over the years, and recognizes the legacy of his many contributions. Dr. Elmaghraby is a pioneer in the area of project scheduling (in particular, project planning and control through network models, for which he coined the term 'activity networks'.) In his initial work in this area, he developed an algebra based on signal flow graphs and semi-Markov processes for analyzing generalized activity networks involving activities with probabilistic durations. This work led to the development of what was later known as the Graphical Evaluation and Review Technique (GERT), and GERT simulation models. He has made fundamental contributions in determining criticality indices for activities, in developing methodologies for project compression and time/cost analysis, and in the use of stochastic and chance-constrained programming and Petri Nets for the analysis of activity networks. This volume brings together fourteen contributions, which can be viewed under the following three main themes: operations research and its application in production planning; project scheduling, and production scheduling, inspired by, and in many cases based on, Dr. Elmaghraby's work in these areas. The first five chapters are devoted to the first theme, followed by four chapters each devoted to the other two, respectively. An additional chapter is devoted to the vulnerability of multimodal freight systems.

This book contains twelve selected papers presented at the International Workshop on Traffic Data Collection and its Standardization held on September 8-9th 2008 in Barcelona. Organized and chaired by Barcelo and Kuwahara, the workshop was intended to examine the purposes and quality of data and how it is collected and used in traffic analysis, with the overall intent of improving and standardizing the practice.

Traffic data is the cornerstone to everything from the most classical traffic control analysis to the most advanced real-time control and management implementing modern Intelligent Transportation Systems (ITS) applications. These applications are primarily based on the availability of traffic data supplied by a Data Collection System which, equipped with more or less sophisticated technologies, provides measurements on the fundamental traffic variables, ideally with the required level of temporal aggregation, and perhaps, when the technology allows it, additional measurements on other variables of interest, depending on the type of application in which they will be used. The applications are in turn supported by models, and in fact the primary use of the data is to provide the input to traffic models whose quality depends on the quality, consistency, robustness, completion and other characteristics of the data.

The main papers presented at the workshop dealt with

• which kind of data are available and under what conditions,

• what kind of data are needed for
• • online applications
  • model calibration/validation
  • safety analysis
• data source reliability
• how standardization can accelerate developments in the field, and how traffic data can be accessed more easily

The papers presented, from which the final twelve were chosen:

1. Calibrating the Fundamental Diagram in Congestion: Methods Based on Observations at Consecutive Loop-Detectors

2. Nicolas Chiabaut, Ludovic Leclercq, Tiphaine Bretin, Christine Buisson

   Universite de Lyon, INRETS / ENTPE, LICIT,

3. A cost-effective Method for the Detection of Queue Lengths at Traffic Lights

Thorsten Neumann

German Aerospace Center, Institute of Transportation Systems

3. Fusing Road Travel Time Data

F. Soriguera CENIT Center for Innovation in Transport, Technical

University of Catalonia (UPC)

D. Abeijon, CENIT Center for Innovation in Transport, Technical University of Catalonia (UPC),

F. Robuste, School of Civil Engineering, Technical University of Catalonia

1. Floating Car Data Based Analysis of Urban Travel Times for the Provision of Traffic Quality

2. Jan Fabian Ehmke, Stephan Meisel, Dirk Christian Mattfeld, Universitat Braunschweig, Carl-Friedrich Gauss Department, Business Information Systems, Decision Support Group

3. Extended Floating Car Data in cooperative traffic management

4. Thomas Scheider, Martin Bohm, AustriaTech,

5. Long-term Investigations of Quality and Reliability of the Video Image Detection System m3

6. Ralf Reulke, Beate Meffert, Bjorn Piltz

   Humboldt-Universitat zu Berlin,

   Sascha Bauer, Daniel Hein, Marc Hohloch, Karsten Kozempel

   German Aerospace Center, Institute for Transportation Systems,

7. Data Mining For Traffic Flow Analysis: Visualization Approach

8. Takahiko KUSAKABE, Takamasa IRYO, Yasuo ASAKURA

   Graduate School of Engineering, Kobe University

9. Microscopic data collection method for analyzing driving behavior at traffic signals

10. Francesco Viti, Serge P. Hoogendoorn, Henk J. van Zuylen

    Delft University of Technology

    Isabel R. Wilmink, Bart van Arem

    TNO, business unit Mobility & Logistics,

11. Data Collection for Measuring Performance of an Integrated Transportation System

12. Wei-Bin Zhang, Alex Skabardonis, Meng Li, Jingquan Li, Kun Zhou, Liping Zhang

    California PATH Program, University of California at Berkeley,

13. Data Requirements for Experimental and Operational Validations of Real-time Traffic Simulation Tools

14. Christine BUISSON, Aurelien DURET

    Universite de Lyon, ENTPE-INRETS, Laboratoire d Ingenierie Circulation Transports LICIT.

15. Parameterization of distribution using survey data: The influence of spatial factors on commuting trips in The Netherlands

16. Tom Thomas, Bas Tutert

    University of Twente, The Netherlands

17. Using floating car data for traffic state estimation in signalized urban networks

18. Henk van Zuylen, Yusen Chen, Fangfang Zheng

    Delft University of Technology

19. Exploring floating car data as a-priori information to dynamic origin destination matrix estimation

20. Yusen Chen, Henk van Zuylen, Runa Asmundsdottir

    Delft University of Technology

21. Data Collection, Use and Provision at the Transport Data Centre, New South Wales, Australia

22. Peter Hidas

    Manager, Transport Model Application Transport Data Centre, NSW Ministry of Transport

23. Hysteresis in the fundamental diagram: impact of measurement methods

24. Jorge A. Laval

    School of Civil and Environmental Engineering, Georgia Institute 4 of Technology

25. Notes on traffic data, traffic applications and traffic models

26. Jaume Barcelo, Dept. of Statistics and Operations Research,

    Technical University of Catalonia

27. Standardising Traffic Data Managed by a Road Authority

28. Stuart Ballingall, Manager Road Information Services, VicRoads

29. International Traffic Data Base

Mark Miska, Masao Kuwahara, University of Tokyo"

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.

This book opens the door to multiobjective optimization for students in fields such as engineering, management, economics and applied mathematics. It offers a comprehensive introduction to multiobjective optimization, with a primary emphasis on multiobjective linear programming and multiobjective integer/mixed integer programming. A didactic book, it is mainly intended for undergraduate and graduate students, but can also be useful for researchers and practitioners. Further, it is accompanied by an interactive software package - developed by the authors for Windows platforms - which can be used for teaching and decision-making support purposes in multiobjective linear programming problems. Thus, besides the textbook's coverage of the essential concepts, theory and methods, complemented with illustrative examples and exercises, the computational tool enables students to experiment and enhance their technical skills, as well as to capture the essential characteristics of real-world problems.

This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.

This book explores the methodological and application developments of network design in transportation and logistics. It identifies trends, challenges and research perspectives in network design for these areas. Network design is a major class of problems in operations research where network flow, combinatorial and mixed integer optimization meet. The analysis and planning of transportation and logistics systems continues to be one of the most important application areas of operations research. Networks provide the natural way of depicting such systems, so the optimal design and operation of networks is the main methodological area of operations research that is used for the analysis and planning of these systems. This book defines the current state of the art in the general area of network design, and then turns to its applications to transportation and logistics. New research challenges are addressed. Network Design with Applications to Transportation and Logistics is divided into three parts. Part I examines basic design problems including fixed-cost network design and parallel algorithms. After addressing the basics, Part II focuses on more advanced models. Chapters cover topics such as multi-facility network design, flow-constrained network design, and robust network design. Finally Part III is dedicated entirely to the potential application areas for network design. These areas range from rail networks, to city logistics, to energy transport. All of the chapters are written by leading researchers in the field, which should appeal to analysts and planners.

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

This book offers an essential review of central theories, current research and applications in the field of numerical representations of ordered structures. It is intended as a tribute to Professor Ghanshyam B. Mehta, one of the leading specialists on the numerical representability of ordered structures, and covers related applications to utility theory, mathematical economics, social choice theory and decision-making. Taken together, the carefully selected contributions provide readers with an authoritative review of this research field, as well as the knowledge they need to apply the theories and methods in their own work.

This book describes a wide range real-case applications of Multi-Criteria Decision Making (MCDM) in maritime related subjects including shipping, port, maritime logistics, cruise ports, waterfront developments, and shipping finance, etc. In such areas, researchers, students and industrialists, in general, felt struggling to find a step-by-step guide on how to apply MCDM to formulate effective solutions to solving real problems in practice. This book focuses on the in-depth analysis and applications of the most well-known MDCM methodologies in the aforementioned areas. It brings together an eclectic collection of twelve chapters which seek to respond to these challenges. The book begins with an introduction and is followed by an overview of major MCDM techniques. The next chapter examines the theory of analytic hierarchy process (AHP) in detail and investigates a fuzzy AHP (FAHP) approach and its capability and rationale in dealing with decision problems of ambiguous information. Chapter 4 proposes a generic methodology to identify the key factors influencing green shipping and to establish an evaluation system for the assessment of shipping greenness. In Chapter 5, the authors describe a new function of fuzzy Evidential Reasoning (ER) to improve the vessel selection process in which multiple criteria with insufficient and ambiguous information are evaluated and synthesized. Chapter 6 presents a novel methodology by using an Artificial Potential Field (APF) model and the ER approach to estimate the collision probabilities of monitoring targets for coastal radar surveillance. Chapter 7 develops the inland port performance assessment model (IPPAM) using a hybrid of AHP, ER and a utility function. The next chapter showcases a challenging approach to address the risk and uncertainty in LNG transfer operations, by utilizing a Stochastic Utility Additives (UTA) method with the help of the philosophy of aggregation-disaggregation coupled with a robustness control procedure. Chapter 9 uses Entropy and Grey Relation Analysis (GRA) to analyze the relative weights of financial ratios through the case studies of the four major shipping companies in Korea and Taiwan: Evergreen, Yang Ming, Hanjin and Hyundai Merchant Marine. Chapter 10 systemically applies modern heuristics to solving MCDM problems in the fields of operation optimisation in container terminals. Arguing that bunkering port selection is typically a multi-criteria group decision problem, and in many practical situations, decision makers cannot form proper judgments using incomplete and uncertain information in an environment with exact and crisp values, in Chapter 11, the authors propose a hybrid Fuzzy-Delphi-TOPSIS based methodology with a sensitivity analysis. Finally, Chapter 12deals with a new conceptual port performance indicators (PPIs) interdependency model using a hybrid approach of a fuzzy logic based evidential reasoning (FER) and a decision making trial and evaluation laboratory (DEMATEL).

This book gathers selected contributions by top Portuguese and international researchers in the field of Operations Research, presented at the 19th Congress of APDIO (Portuguese Association of Operational Research). The papers address a broad range of complex real-world problems, which are approached using recent theoretical techniques. Of particular interest are the applications of e.g. linear, nonlinear and mixed-integer programming, multiobjective optimization, metaheuristics and hybrid heuristics, multicriteria decision analysis, data envelopment analysis, clustering techniques and decision support systems, in such varied contexts as: supply chain management, scheduling problems, production management, logistics, energy, finance and healthcare. This conference, organized by APDIO and held in Aveiro, Portugal in September 2018, offered an ideal opportunity to discuss the latest developments in this field and to build new bridges between academic researchers and practitioners. Summarizing the outcomes, this book offers a valuable tool for all researchers, students and practitioners who wish to learn about the latest trends in this field.

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.

"Everything should be made as simple as possible-but not simpler" Albert Einstein Traffic Theory, like all other sciences, aims at understanding and improving a physical phenomenon. The phenomenon addressed by Traffic Theory is, of course, automobile traffic, and the problems associated with it such as traffic congestion. But what causes congestion? Some time in the 1970s, Doxiades coined the term "oikomenopolis" (and "oikistics") to describe the world as man's living space. In Doxiades' terms, persons are associated with a living space around them, which describes the range that they can cover through personal presence. In the days of old, when the movement of people was limited to walking, an individual oikomenopolis did not intersect many others. The automobile changed all that. The term "range of good" was also coined to describe the maximal distance a person can and is willing to go in order to do something useful or buy something. Traffic congestion is caused by the intersection of a multitude of such "ranges of good" of many people exercising their range utilisation at the same time. Urban structures containing desirable structures contribute to this intersection of "ranges of good." xii Preface In a biblical mood, I opened a 1970 paper entitled "Traffic Control -- From Hand Signals to Computers" with the sentence: "In the beginning there was the Ford."

In May 2002 a number of about 20 scientists from various disciplines were invited by the Berlin-Brandenburg Academy of Sciences and Humanities to participate in an interdisciplinary workshop on structures and structure generating processes. The site was the beautiful little castle of Blankensee, south of Berlin. The disciplines represented ranged from mathematics and information theory, over various ?elds of engineering, biochemistry and biology, to the economic and social sciences. All participants presented talks explaining the nature of structures considered in their ?elds and the associated procedures of analysis. It soon became evident that the study of structures is indeed a common c- cern of virtually all disciplines. The motivation as well as the methods of analysis, however, differ considerably. In engineering, the generation of artifacts, such as infrastructures or technological processes, are of primary interest. Frequently, the analysis aims there at de?ning a simpli?ed mathematical model for the optimization of the structures and the structure generating processes. Mathematical or heuristic methods are applied, the latter preferably of the type of biology based evolutionary algorithms. On the other hand, setting up complex technical structures is not pos- ble by such simpli?ed model calculations but requires a different and less model but rather knowledge-based type of approach, using empirical rules rather than formal equations. In biochemistry, interest is frequently focussed on the structures of molecules, such as proteins or ribonucleic acids. Again, optimal structures can usually be de?ned.

Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems. Fast advances in soft computing technologies, such as fuzzy logic and systems, artificial neural networks and evolutionary computation, have made available powerful problem representation and modelling paradigms, and learning and optimisation mechanisms for addressing modern decision making issues. This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications. Different from other existing books, this volume predominately focuses on applied decision support with soft computing. Areas covered include planning, management finance and administration in both the private and public sectors.

This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together - as chapter contributors - researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors' goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.

In today's global economy, supply chains are an essential ingredient to corporate survival and growth. Operations strategy in supply chains must assume an ever-expanding and strategic role of risks that modern enterprises face when they operate in an interdependent supply chain environment. These operational and strategic facets entail a brand new set of operational problems and risks that have not always been understood or managed very well. It falls to supply chain managers to identify and to educate corporate managers on what these critical operational problems and risks involve. This book provides business students and practitioners with the means to understand, to model and to analyze these outstanding issues and problems that are the essential elements in managing supply chains today. This book will consider these problems in depth and draw essential conclusions regarding their management in supply chains. As a textbook treatment, it will examine traditional operational problems, expressing them in a strategic context, understanding their complexity, and recognizing their interdependency with other firms within a supply-chain environment. Used throughout the book will be application examples that illustrate all the aspects of dealing with and solving these kinds of problems. The content of SUPPLY CHAIN GAMES: Operations Management and Risk Valuation is presented in three sections, each of which will emphasize important facets of supply chain management operations. (1) Supply chains and operations modeling and management section will provide static and time models and their gradual extension to a supply chain environment. The section will give special attention tothe new concerns and issues at this level of analysis. (2) Inter-temporal supply chain management section will address this aspect as differential games. The differential games will be presented as natural continuous-time extensions of static models so that the effect of various types of dynamics on supply chains can be assessed and insights can be developed. (3) Risk and supply chain management section will deal with risk and supply chains as well as providing numerous applications regarding the management of interdependent operations and quality in a supply chain environment.

This book provides a systematic framework for effectively creating value through engineering in global business networks, and contributes to an increasingly important branch of engineering operations. By updating the traditional disciplines of engineering and operations management and addressing challenges and opportunities in building global network capabilities, this study offers a contemporary guide for developing effective industrial policies to enhance the global competitiveness of engineering sectors, which will be extremely useful to engineering companies and policy-makers. Themes discussed include main trends and driving forces, state-of-the-art knowledge in relevant subject areas, new technologies and leading practice. This timely book will help researchers, managers and students to gain an overall understanding of the pioneering research occurring in this field and it will enable companies to benefit from global engineering networks.

This book inclusively and systematically presents the fundamental methods, models and techniques of practical application of grey data analysis, bringing together the authors' many years of theoretical exploration, real-life application, and teaching. It also reflects the majority of recent theoretical and applied advances in the theory achieved by scholars from across the world, providing readers a vivid overall picture of this new theory and its pioneering research activities. The book includes 12 chapters, covering the introduction to grey systems, a novel framework of grey system theory, grey numbers and their operations, sequence operators and grey data mining, grey incidence analysis models, grey clustering evaluation models, series of GM models, combined grey models, techniques for grey systems forecasting, grey models for decision-making, techniques for grey control, etc. It also includes a software package that allows practitioners to conveniently and practically employ the theory and methods presented in this book. All methods and models presented here were chosen for their practical applicability and have been widely employed in various research works. I still remember 1983, when I first participated in a course on Grey System Theory. The mimeographed teaching materials had a blue cover and were presented as a book. It was like finding a treasure: This fascinating book really inspired me as a young intellectual going through a period of confusion and lack of academic direction. It shone with pearls of wisdom and offered a beacon in the mist for a man trying to find his way in academic research. This book became the guiding light in my life journey, inspiring me to forge an indissoluble bond with Grey System Theory. --Sifeng Liu

Virtually all nontrivial and modern service related problems and systems involve data volumes and types that clearly fall into what is presently meant as "big data", that is, are huge, heterogeneous, complex, distributed, etc. Data mining is a series of processes which include collecting and accumulating data, modeling phenomena, and discovering new information, and it is one of the most important steps to scientific analysis of the processes of services. Data mining application in services requires a thorough understanding of the characteristics of each service and knowledge of the compatibility of data mining technology within each particular service, rather than knowledge only in calculation speed and prediction accuracy. Varied examples of services provided in this book will help readers understand the relation between services and data mining technology. This book is intended to stimulate interest among researchers and practitioners in the relation between data mining technology and its application to other fields.

Globalization has created an increase in the number of business opportunities presented to enterprises. A competitive market places demands on businesses to think differently and follow new approaches to managing their business goals and remaining acceptable to suppliers and service providers. Effective Open Innovation Strategies in Modern Business: Emerging Research and Opportunities is a comprehensive resource that focuses on the importance of interdisciplinary concepts in open innovation projects. Using case illustrations, the book examines concepts such as virtual reality, knowledge harvesting, and business process reengineering in relation to open innovation initiatives. As a publication exploring the areas of management and information technology disciplines, this resource is useful for corporate executives, business managers, entrepreneurs, business professionals, and graduate-level students seeking current research on business innovation techniques and approaches.

Aviation networks play a critical role in the success of today's airlines and airports. This book provides insight on all aspects of modern network strategies and structures, ranging from market research to hub design, operations, organization, alliances, benchmarking, and antitrust issues. Considering both the airline and the airport perspectives, the book explains the economics of connectivity or productivity-driven hub structures through basic mathematics, which helps the reader to comprehend the structural strengths and weaknesses of aviation networks. More than 100 charts help clarify the topics at hand.

Like norms, translation invariant functions are a natural and powerful tool for the separation of sets and scalarization. This book provides an extensive foundation for their application. It presents in a unified way new results as well as results which are scattered throughout the literature. The functions are defined on linear spaces and can be applied to nonconvex problems. Fundamental theorems for the function class are proved, with implications for arbitrary extended real-valued functions. The scope of applications is illustrated by chapters related to vector optimization, set-valued optimization, and optimization under uncertainty, by fundamental statements in nonlinear functional analysis and by examples from mathematical finance as well as from consumer and production theory. The book is written for students and researchers in mathematics and mathematical economics. Engineers and researchers from other disciplines can benefit from the applications, for example from scalarization methods for multiobjective optimization and optimal control problems.