Global supply chain has continued to gain great attention in recent decades due to globalization and economic policies by companies striving to gain bigger market share and countries that make every effort for a freer trade. The concept of supply chain has evolved progressively over time, from simple supplier systems with one or two suppliers to global chains with complex networks of suppliers, vendors, warehouses, manufacturers, shippers, wholesalers, and/or retailers. Customer-Oriented Global Supply Chains: Concepts for Effective Management provides insights and support executives, middle managers, and practitioners concerned with the management of supply chain with expertise, knowledge, information, and organizational management development in different types of industries. The book is a collection of knowledge that will assist researchers, teachers, students, and practitioners in enhancing their understanding of global supply chain management and solutions applied.

This handbook provides an innovative, thorough overview of service management. It draws together an impressive, international group of leading scholars who offer a truly global perspective, exploring current literature and laying out guidance for future research. Beginning with defining service as a perspective on value creation, and service management as "a set of organizational competencies for enabling and realizing value creation through service," it then moves on to follow the evolution of service research. From there, the book is structured into six main themes: perspectives on service management; service strategy; service leadership and transition; service design and innovation; service interaction; quality and operations; and service management and technology. This book is valuable reading for academics, lecturers, and students studying service management, operations management, and service research.

This book presents the latest developments and breakthroughs in fuzzy theory and performance prediction of queuing and reliability models by using the stochastic modeling and optimization theory. The main focus is on analytics that use fuzzy logic, queuing and reliability theory for the performance prediction and optimal design of real-time engineering systems including call centers, telecommunication, manufacturing, service organizations, etc. For the day-to-day as well as industrial queuing situations and reliability prediction of machining parts embedded in computer, communication and manufacturing systems, the book assesses various measures of performance and effectiveness that can provide valuable insights and help arrive at the best decisions with regard to service and engineering systems. In twenty chapters, the book presents both theoretical developments and applications of the fuzzy logic, reliability and queuing models in a diverse range of scenarios. The topics discussed will be of interest to researchers, educators and undergraduate students in the fields of Engineering, Business Management, and the Mathematical Sciences.

This book offers a comprehensive and systematic introduction to the latest research on hesitant fuzzy decision-making theory. It includes six parts: the hesitant fuzzy set and its extensions, novel hesitant fuzzy measures, hesitant fuzzy hybrid weighted aggregation operators, hesitant fuzzy multiple-criteria decision-making with incomplete weights, hesitant fuzzy multiple criteria decision-making with complete weights information, and the hesitant fuzzy preference relation based decision-making theory. These methodologies are implemented in various fields such as decision-making, medical diagnosis, cluster analysis, service quality management, e-learning management and environmental management. A valuable resource for engineers, technicians, and researchers in the fields of fuzzy mathematics, operations research, information science, management science and engineering, it can also be used as a textbook for postgraduate and senior undergraduate students.

Increasingly, multimedia content from music, movies, games, news, books, and digital art to sharable educational material, e-government services, and e-health services is delivered over broadband networks. With technological advances, cloud computing applications, and social networking approaches, many exciting applications are emerging to deliver this content as Interactive Digital Media (IDM). Understanding the Interactive Digital Media Marketplace: Frameworks, Platforms, Communities and Issues presents the results of a large, industry-oriented, multi-national research program. This research seeks to discover usable business models, technology platforms, market strategies and policy frameworks for the emerging global digital economy, particularly for digital media researchers and industry entrepreneurs who wish to reach users around the world.

The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.

This volume contains two types of papers-a selection of contributions from the "Second International Conference in Network Analysis" held in Nizhny Novgorod on May 7-9, 2012, and papers submitted to an "open call for papers" reflecting the activities of LATNA at the Higher School for Economics. This volume contains many new results in modeling and powerful algorithmic solutions applied to problems in * vehicle routing * single machine scheduling * modern financial markets * cell formation in group technology * brain activities of left- and right-handers * speeding up algorithms for the maximum clique problem * analysis and applications of different measures in clustering The broad range of applications that can be described and analyzed by means of a network brings together researchers, practitioners, and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The contributions not only come from different fields, but also cover a broad range of topics relevant to the theory and practice of network analysis. Researchers, students, and engineers from various disciplines will benefit from the state-of-the-art in models, algorithms, technologies, and techniques presented.

This book demonstrates the power of neural networks in learning complex behavior from the underlying financial time series data. The results presented also show how neural networks can successfully be applied to volatility modeling, option pricing, and value-at-risk modeling. These features mean that they can be applied to market-risk problems to overcome classic problems associated with statistical models.

The Analytic Hierarchy Process (AHP) is a prominent and powerful tool for making decisions in situations involving multiple objectives. Models, Methods, Concepts and Applications of the Analytic Hierarchy Process, 2nd Edition applies the AHP in order to solve problems focused on the following three themes: economics, the social sciences, and the linking of measurement with human values. For economists, the AHP offers a substantially different approach to dealing with economic problems through ratio scales. Psychologists and political scientists can use the methodology to quantify and derive measurements for intangibles. Meanwhile researchers in the physical and engineering sciences can apply the AHP methods to help resolve the conflicts between hard measurement data and human values. Throughout the book, each of these topics is explored utilizing real life models and examples, relevant to problems in today's society. This new edition has been updated and includes five new chapters that includes discussions of the following: - The eigenvector and why it is necessary - A summary of ongoing research in the Middle East that brings together Israeli and Palestinian scholars to develop concessions from both parties - A look at the Medicare Crisis and how AHP can be used to understand the problems and help develop ideas to solve them.

This book provides an introduction to vector optimization with variable ordering structures, i.e., to optimization problems with a vector-valued objective function where the elements in the objective space are compared based on a variable ordering structure: instead of a partial ordering defined by a convex cone, we see a whole family of convex cones, one attached to each element of the objective space. The book starts by presenting several applications that have recently sparked new interest in these optimization problems, and goes on to discuss fundamentals and important results on a wide range of topics. The theory developed includes various optimality notions, linear and nonlinear scalarization functionals, optimality conditions of Fermat and Lagrange type, existence and duality results. The book closes with a collection of numerical approaches for solving these problems in practice.

This book develops and assesses a decision-making model for resource management in complex work systems in line with the "Systems Engineering" method. It applies the Balanced Scorecard to the development of the criteria system for decision-making, and employs fuzzy linguistics theory to evaluate the alternatives. Further, the book assesses the application of this model in a hospital that has to decide whether or not to outsource its sterile goods. The use of the model opens up a diverse range of fields for decision-making in the area of complex work systems.

This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on July 30-August 1, 2012. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of optimization techniques in finance, logistics, health, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.

This book analyzes the underlying theoretical principles of multi-objective linear programming problems with multi-choice parameters. It studies transportation problems on the same domain with extension to fuzzy stochastic criteria, and offers insights into sensitivity analysis through symmetric duality and complementarity using non-convex programming. These analytical presentations provide ample scope for researchers to contemplate real-world problems with an innovative vision. The formulation, analysis and solution procedures on inventory control models in the book use both deterministic and fuzzy parameters, and provide novel optimal inventory policies. The book discusses a wide range of optimal operational techniques for policy makers, government and private agencies in the fields of e-governance and agricultural crop insurance, which are crucial for developing countries. The recommendations address the gaps and remedies in various schemes that influence decision-making in the context of the economic development of such countries.

This book describes how a model for optimizing the energy supply system in Germany can be implemented. It focuses on the open energy modeling framework (Oemof) program for modeling energy supply systems. The individual elements of Oemof are described, as well as the model's structure. The technical components of Oemof are subsequently demonstrated in mathematical calculations, along with sufficient Python code to begin basic modeling. The book will appeal to anyone with an interest in optimization models for energy supply systems, or in the mathematical description of the technical components of such systems in practical implementation, using a real example, Oemof. Thermodynamic descriptions of combustion are provided, so that readers can focus on modeling aspects. Researchers and practitioners will also find the book useful, as it expands on their knowledge of the technical components of energy supply systems, supported with detailed mathematical calculations.

Putting forward a unified presentation of the features and possible applications of probabilistic preferences composition, and serving as a methodology for decisions employing multiple criteria, this book maximizes reader insights into the evaluation in probabilistic terms and the development of composition approaches that do not depend on assigning weights to the criteria. With key applications in important areas of management such as failure modes, effects analysis and productivity analysis - together with explanations about the application of the concepts involved -this book makes available numerical examples of probabilistic transformation development and probabilistic composition. Useful not only as a reference source for researchers, but also in teaching classes of graduate courses in Production Engineering and Management Science, the key themes of the book will be of especial interest to researchers in the field of Operational Research.

This is the Proceedings of the Eighth International Conference on Management Science and Engineering Management (ICMSEM) held from July 25 to 27, 2014 at Universidade Nova de Lisboa, Lisbon, Portugal and organized by International Society of Management Science and Engineering Management (ISMSEM), Sichuan University (Chengdu, China) and Universidade Nova de Lisboa (Lisbon, Portugal). The goals of the conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current findings. A total number of 138 papers from 14 countries are selected for the proceedings by the conference scientific committee through rigorous referee review. The selected papers in the first volume are focused on Intelligent System and Management Science covering areas of Intelligent Systems, Decision Support Systems, Manufacturing and Supply Chain Management.

This guide is designed for systems researchers - emerging and seasoned - searching for holistic approaches of inquiry into complexity, which the Systems Sciences provide. The authors share insight into the foundations of research that are not only systematic in terms of rigor, but systemic in perspective, analysis, design, development, implementation, reporting, and evaluation. This guide also explores researcher competencies necessary to conduct sound systems research. Researchers using this guide will gain understanding of what distinguishes systems research from other types of research and why it is important in research today.

Risk and reward are always foremost in the determination of investment decisions and business transactions. Advances in the area of Information Communication Technologies (ICT) have enabled the development of new business paradigms. Such paradigms involve transactions taking place between loosely connected parties, often totally or partially unknown to one another. One important concept required to ensure such transactions are successful is transactional risk. The importance of doing this has been demonstrated in recent financial crisis. This book is unique in simultaneously taking into account the likelihood of an event occurring and its financial impact and provides an integrated discussion of the process of transactional risk identification, assessment, evaluation, management and recording in these emerging domains. It provides a detailed and clear exposition of the importance of transactional risk before detailing for its assessment and evaluation. The scope of the book is theoretical and practical and as such it will have a broad market both within academia and industry. Specifically this book should be of primary interest to researchers, graduate students and practitioners in the area of developing business intelligence techniques and their application in various real world applications.

This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.

This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.

Scheduling theory has received a growing interest since its origins in the second half of the 20th century. Developed initially for the study of scheduling problems with a single objective, the theory has been recently extended to problems involving multiple criteria. However, this extension has still left a gap between the classical multi-criteria approaches and some real-life problems in which not all jobs contribute to the evaluation of each criterion.

In this book, we close this gap by presenting and developing multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. Several scenarios are introduced, depending on the definition and the intersection structure of the job subsets. Complexity results, approximation schemes, heuristics and exact algorithms are discussed for single-machine and parallel-machine scheduling environments. Definitions and algorithms are illustrated with the help of examples and figures.

The International Civil Aviation Organization's (ICAO) decision to require aviation organizations to adopt Safety Management Systems poses a major problem especially for small and medium sized aviation companies. The complexity of regulations overstrains the aviation stakeholders who seek to fully advantage from them but have no clear guidance. The aim of the book is to show the implementation of such a new system with pragmatic effort in order to gain a gradation for smaller operators. This approach should illustrate the leeway in order to adapt the processes and to show the interfaces between Corporate Risk Management and Safety Management. The book shows how to build a system with reasonable effort, appropriate to the size and complexity of the specific operator. It also gives inputs on the key aspects and how to effectively operate such a system with the various interfaces. Furthermore, the book highlights the importance of Corporate Risk Management independent of Safety Management Systems based on ICAO.

This book describes five qualitative investment decision-making methods based on the hesitant fuzzy information. They are: (1) the investment decision-making method based on the asymmetric hesitant fuzzy sigmoid preference relations, (2) the investment decision-making method based on the hesitant fuzzy trade-off and portfolio selection, (3) the investment decision-making method based on the hesitant fuzzy preference envelopment analysis, (4) the investment decision-making method based on the hesitant fuzzy peer-evaluation and strategy fusion, and (5) the investment decision-making method based on the EHVaR measurement and tail analysis.

Dynamics of Information Systems: Algorithmic Approaches presents recent developments and results found by participants of the Fourth International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 20-22, 2012. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems. Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: detection of terrorist networks, design of highly efficient businesses, computer networks, quantum entanglement, genome modeling, multi-robotic systems, and industrial and manufacturing safety. The book contains state-of-the-art work on theory and practice relevant to the dynamics of information systems. It covers algorithmic approaches to numerical computations with infinite and infinitesimal numbers; presents important problems arising in service-oriented systems, such as dynamic composition and analysis of modern service-oriented information systems and estimation of customer service times on a rail network from GPS data; addresses the complexity of the problems arising in stochastic and distributed systems; and discusses modulating communication for improving multi-agent learning convergence. Network issues-in particular minimum-risk maximum-clique problems, vulnerability of sensor networks, influence diffusion, community detection, and link prediction in social network analysis, as well as a comparative analysis of algorithms for transmission network expansion planning-are described in later chapters.

Counting belongs to the most elementary and frequent mental activities of human beings. Its results are a basis for coming to a decision in a lot of situations and dimensions of our life. This book presents a novel approach to the advanced and sophisticated case, called intelligent counting, in which the objects of counting are imprecisely, fuzzily specified. Formally, this collapses to counting in fuzzy sets, interval-valued fuzzy sets or I-fuzzy sets (Atanassov's intuitionistic fuzzy sets). The monograph is the first one showing and emphasizing that the presented methods of intelligent counting are human-consistent: are reflections and formalizations of real, human counting procedures performed under imprecision and, possibly, incompleteness of information. Other applications of intelligent counting in various areas of intelligent systems and decision support will be discussed, too. The whole presentation is self-contained, systematic, and equipped with many examples, figures and tables. Computer and information scientists, researchers, engineers and practitioners, applied mathematicians, and postgraduate students interested in information imprecision are the target readers.