This book recapitulates the major developments in Decision Support Systems (DSS) over the last 30 years in order to evaluate the research areas of decision making and in which direction the field should proceed. As it attempts to find a consensus about the next steps for the future of DSS research, the book also enforces the trends and new technologies currently in use. The book examines topics such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluation and analysis through social networks, and e-learning and its application to real environments. It clearly presents the evidence to support their cases and attempts to promote an extensive and objective discussion. In addition, the book also reflects on approaches to dead-end ideas and failures in DSS to better understand the lessons learned. The contributions for this book have been written by thought leaders and influential researchers from the EURO Working Group of Decision Support Systems (EWG-DSS).

This book explains the theoretical structure of particle swarm optimization (PSO) and focuses on the application of PSO to portfolio optimization problems. The general goal of portfolio optimization is to find a solution that provides the highest expected return at each level of portfolio risk. According to H. Markowitz's portfolio selection theory, as new assets are added to an investment portfolio, the total risk of the portfolio's decreases depending on the correlations of asset returns, while the expected return on the portfolio represents the weighted average of the expected returns for each asset. The book explains PSO in detail and demonstrates how to implement Markowitz's portfolio optimization approach using PSO. In addition, it expands on the Markowitz model and seeks to improve the solution-finding process with the aid of various algorithms. In short, the book provides researchers, teachers, engineers, managers and practitioners with many tools they need to apply the PSO technique to portfolio optimization.

This book presents the human, cultural, and scientific contributions of professor Eliano Pessa, who recently passed away. His research interests and activities were varied, some of which included quantum physics, cognitive science and psychology, systems science, artificial intelligence, and alpinism. They were never disciplinary-separated issues, but rather some coherent dimensions of his interests in life. He lived and not only practiced interdisciplinarity and multiple dimensions; he considered it unacceptable to do only one thing in life. The contributors in this volume consider, discuss, interpret, and represent the multiplicity and interdisciplinarity experienced, lived and applied by Pessa. The chapters are inspired by, rebuild, and retrace such networked interests lived by him from the personal, cultural, and scientific points of view of the authors. This is true interdisciplinarity and usage of non-equivalences, honoring the richness of Pessa's contributions.

This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine learning as a discipline would not be possible without the inner workings of optimization at hand. The book includes the necessary sinews of optimization though the crux of the discussion centers on the increasingly popular tool for training deep learning models, namely synthetic data. It is expected that the field of synthetic data will undergo exponential growth in the near future. This book serves as a comprehensive survey of the field. In the simplest case, synthetic data refers to computer-generated graphics used to train computer vision models. There are many more facets of synthetic data to consider. In the section on basic computer vision, the book discusses fundamental computer vision problems, both low-level (e.g., optical flow estimation) and high-level (e.g., object detection and semantic segmentation), synthetic environments and datasets for outdoor and urban scenes (autonomous driving), indoor scenes (indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision (in neural programming, bioinformatics, NLP, and more). It also surveys the work on improving synthetic data development and alternative ways to produce it such as GANs. The book introduces and reviews several different approaches to synthetic data in various domains of machine learning, most notably the following fields: domain adaptation for making synthetic data more realistic and/or adapting the models to be trained on synthetic data and differential privacy for generating synthetic data with privacy guarantees. This discussion is accompanied by an introduction into generative adversarial networks (GAN) and an introduction to differential privacy.

This book offers an introduction to various models and methods for green supplier evaluation and selection (GSES) within different information settings. As such, it provides valuable knowledge, useful GSES methods and practical examples that can be considered by manufacturers in selecting appropriate green suppliers to improve their environmental performance and customer satisfaction. This book is useful for practitioners and researchers working in the fields of supply chain management, operation management, information science, industrial engineering, and management science. It is also useful as a textbook for postgraduate and senior undergraduate students.

This book focuses on decision-making problems in engineering. It investigates the ranking aggregation problem and the related features, such as input/output data, simplification hypotheses, importance hierarchy of experts. In addition to a well-structured overview of several interesting, consolidated methodological approaches, it presents innovative approaches that can also be applied profitably in other fields. The fascinating selection of topics included is based on research that has been developed in the past twenty years. The descriptions are supported by figures, tables, flowcharts, diagrams, examples and practical case studies. The book is an ideal resource for engineering academics, practitioners, technicians and students, who do not necessarily have an in-depth knowledge of decision-making. It is also a thought-provoking read for engineers and academics looking for innovative ways to improve engineering processes in a variety of fields, such as conceptual design, quality improvement, reliability engineering. "Today, rankings are exercised in all spheres of life, products are ranked on Amazon and similar platforms; services such as restaurants and hotels on platforms such as TripAdvisor; and other services such as lectures or even medical treatment on different specialized platforms. We often make our daily decisions based on these rankings. The quality of our decisions depends on our ability to select appropriate methods to fit the context and needs. We need to be familiar with the theory and practice of these methods to make them useful. To this purpose, this book is an important addition to the bookshelves of academics and professionals, not only from engineering. The connection between theory and practice is weaved throughout the book, making it useful for practitioners also." Prof. Yoram Reich, Full Professor and Head of Systems Engineering research Initiative at Tel Aviv University (Israel), Editor-in-Chief of "Research in Engineering Design"

This book provides relevant theoretical frameworks and the latest empirical research findings of Operations Research/Management Science applied to Internet of Things. This book identifies and describes ways in which OR and MS have been applied and influenced the development of IoT. Examples are from smart industry; city; transportation; home and smart devices. It discusses future applications, trends, and potential benefits of this new discipline. It is written for professionals who want to improve their understanding of the strategic role of IoT at various levels of the organization, that is, IoT at the global economy level, at networks and organizations level, at teams and work groups, at information systems and, finally, IoT at the level of individuals, as players in the networked environments.

This book gathers selected peer-reviewed papers from the 16th World Congress on Engineering Asset Management (WCEAM), held in Seville from 5-7 October 2022. This book covers a wide range of topics in Engineering Asset Management, including: Asset management and decision support system Industry 4.0 tools and its impact on asset management Monitoring, diagnostics and prognostics for smart maintenance Asset life cycle management Asset management in the industrial sector Human dimensions and asset management performance Infrastructure Asset management Asset condition, risk, resilience, and vulnerability assessments Asset operations and maintenance strategies Reliability and resilience engineering Applications of international and local guidelines and standards The breadth and depth of this state-of-the-art, comprehensive proceedings make it an excellent resource for asset management practitioners, researchers and academics, as well as undergraduate and postgraduate students.

From the Foreword by Marshall Fisher, The Wharton School, University of Pennsylvania: As generation of academics and practitioners follows generation, it is worthwhile to compile long views of the research and practice in the past to shed light on research and practice going forward. This collection of peer-reviewed articles is intended to provide such a long view. This book contains a collection of chapters written by leading scholars/practitioners who have continued their efforts in developing and/or implementing innovative OR/MS tools for solving real world problems. In this book, the contributors share their perspectives about the past, present and future of OR/MS theoretical development, solution tools, modeling approaches, and applications. Specifically, this book collects chapters that offer insights about the following topics: * Survey articles taking a long view over the past two or more decades to arrive at the present state of the art while outlining ideas for future research. Surveys focus on use of a particular OR/MS approach, e.g., mathematical programming (LP, MILP, etc.) and solution methods for particular family of application, e.g., distribution system design, distribution planning system, health care. * Autobiographical or biographical accounts of how particular inventions (e.g., Structured Modeling) were made. These could include personal experiences in early development of OR/MS and an overview of what has happened since. * Development of OR/MS mathematical tools (e.g., stochastic programming, optimization theory). * Development of OR/MS in a particular industry sector such as global supply chain management. * Modeling systems for OR/MS and their development over time as well as speculation on future development (e.g., LINDO, LINGO, and What'sBest!) * New applications of OR/MS models (e.g., happiness) The target audience of this book is young researchers, graduate/advanced undergraduate students from OR/MS and related fields like computer science, engineering, and management as well as practitioners who want to understand how OR/MS modeling came about over the past few decades and what research topics or modeling approaches they could pursue in research or application.

Seaport Container Terminals (SCT) operate as central nodes in worldwide hub-and-spoke networks, and link ocean-going vessels with smaller feeder vessels, as well as with inbound and outbound hinterland transportation systems using road, rail, or inland waterways. The volume of transcontinental container flows has gained enormously over the last five decades frequently leading to double-digit annual growth rates for the SCT. The 2nd edition of the Handbook of Terminal Planning also deals with problems being induced by questions of terminal development on a long-term basis (strategic level). Facing present and upcoming challenges for SCT operation-such as more and more mega vessels, extremely high hinterland peaks, higher environmental standards, less public acceptance and the stronger competition between terminals serving the same hinterland-the focus of the book is on successful approaches and solutions primarily addressing the planning of terminal structures. Nevertheless, operational aspects are considered, as well as how they effectively contribute to problem solving on the strategic level.

This book offers an introduction to structural dynamics, ripple effect and resilience in supply chain disruption risk management for larger audiences. In the management section, without relying heavily on mathematical derivations, the book offers state-of-the-art concepts and methods to tackle supply chain disruption risks and designing resilient supply chains in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering background. In the technical section, the book constitutes structural dynamics control methods for supply chain management. Real-life problems are modelled and solved with the help of mathematical programming, discrete-event simulation, optimal control theory, and fuzzy logic. The book derives practical recommendations for management decision-making with disruption risk in the following areas: How to estimate the impact of possible disruptions on performance in the pro-active stage? How to generate efficient and effective stabilization and recovery policies? When does one failure trigger an adjacent set of failures? Which supply chain structures are particular sensitive to ripple effect? How to measure the disruption risks in the supply chain?

An Annotated Timeline of Operations Research: An Informal History recounts the evolution of Operations Research (OR) as a new science - the science of decision making. Arising from the urgent operational issues of World War II, the philosophy and methodology of OR has permeated the resolution of decision problems in business, industry, and government. The Timeline chronicles the history of OR in the form of self-contained, expository entries. Each entry presents a concise explanation of the events and people under discussion, and provides key sources where further relevant information can be obtained. In addition, books and papers that have influenced the development of OR or helped to educate the first generations of OR academics and practitioners are cited throughout the book. Starting in 1564 with seminal ideas that form the precursors of OR, the Timeline traces the key ideas and events of OR through 2004.
The Timeline should interest anyone involved in OR - researchers, practitioners, academics, and, especially, students - who wish to learn how OR came into being. Further, the scope and expository style of the Timeline should make it of value to the general reader interested in the development of science and technology in the last half of the twentieth century.

The encounter, in the late seventies, between the theory of triangular norms, issuing frorn stochastic geornetry, especially the works of Menger, Schweizer and Sklar, on the one band, and the theory of fuzzy sets due to Zadeh, 10n the other band has been very fruitful. Triangular norms have proved to be ready-rnade mathematical rnodels of fuzzy set intersections and have shed light on the algebraic foundations of fuzzy sets. One basic idea behind the study of triangular norms is to solve functional equations that stern frorn prescribed axioms describing algebraic properties such as associativity. Alternative operations such as rneans have been characterized in a similar way by Kolmogorov, for instance, and the rnethods for solving functional equations are now weil established thanks to the efforts of Aczel, among others. One can say without overstaternent that the introduction of triangular norms in fuzzy sets has strongly influenced further developrnents in fuzzy set theory, and has significantly contributed to its better acceptance in pure and applied rnathematics circles. The book by Fodor and Roubens systematically exploits the benefits of this encounter in the- analysis of fuzzy relations. The authors apply functional equation rnethods to notions such as equivalence relations, and various kinds of orderings, for the purpose of preference rnodelling. Centtal to this book is the rnultivalued extension of the well-known result claiming that any relation expressing weak preference can be separated into three cornponents respectively describing strict preference, indifference and incomparability.

The book discusses the study and implementation of controlling in the modern enterprise from the perspective of Industry 4.0, which helps ensure the efficient and effective use of organizational resources in order to achieve planned goals. The aim of this book is to provide the most comprehensive and effective exchange of information on current developments in Enterprise Controlling. The authors describe lean/agile approaches that enterprises can use to reach the highest level of competitiveness in a global environment and help establish channels of communication and disseminate knowledge among professionals working in manufacturing and related institutions. The authors aim to help facilitate corporate coordination and help with its planning without deviating from standards. The publication is dedicated to all who want to learn in the field of controlling from researchers and academics to students.

This book presents various multi-criteria analysis methods for sustainability-oriented analysis and decision-making for energy systems, under various different conditions and scenarios. It presents methodologies to answer the questions relating to which of the options are the most sustainable among the alternatives, and how multi-criteria decision analysis methods can be used to select the most sustainable energy systems. A systematic innovative methodological framework is presented, which enables the most appropriate energy system to be selected under different conditions including: Scientific decision support tools for sustainable energy system selection; Fuzzy, grey, and rough sets based multi-criteria decision analysis; Decision-making models under uncertainties; and The combination of life cycle thinking and multi-criteria decision analysis This book is of interest to researchers, engineers, decision makers, and postgraduate students within the field of energy systems, sustainability, and multi-criteria decision analysis.

This volume offers the state-of-the-art research and developments in service science and related research, education and practice areas. It showcases emerging technology and applications in fields including healthcare, energy, finance, information technology, transportation, sports, logistics, and public services. Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users' both utilitarian and socio-psychological needs. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions. Chapters highlight ways to approach such technical challenges in service science and are based on submissions from the 2020 INFORMS International Conference on Service Science.

This book is the first comprehensive tutorial on matheuristics. Matheuristics are based on mathematical extensions of previously known heuristics, mainly metaheuristics, and on original, area-specific approaches. This tutorial provides a detailed discussion of both contributions, presenting the pseudocodes of over 40 algorithms, abundant literature references, and for each case a step-by-step description of a sample run on a common Generalized Assignment Problem example. C++ source codes of all algorithms are available in an associated SW repository.

Operations may not run the world but make the world run! Learn how a business operates and improves its processes from some of the leading experts in the field. Operations Management, 10th edition is the ultimate guide on the subject, providing you with the best ways and strategies to learn, explore and make sense of how a business works, coming from world-leading experts Nigel Slack, Alistair Brandon-Jones, and Nicola Burgess. Strategic in its perspective and with a clear structure, the latest edition offers a comprehensive and practical way to study key concepts surrounding effective operation processes, from theory to practice. What makes Operations Management, 10th edition work so well? Clear structure, thanks to the "4 Ds" model of Operations Management. Real-life examples that are shown in the "Operations in Practice" boxes and case studies. Worked examples that blend qualitative and quantitative perspectives. Critical commentaries, posing alternative views where appropriate. Summary provided in practical bullet points, answering key questions. A new section in every chapter called "Responsible Operations", that summarises how the topic touches upon social, ethical, and environmental issues. With plenty of new end-of-chapter case studies and a plethora of international examples, this textbook will challenge your critical thinking, both individually and as part of your group discussion in class. Along with the practice cases, summaries, and illustrations, this edition is the definitive guide for your studies in the field of Operations Management. Pearson, the world's learning company.

The well-ordered, fully aligned view of organization and management practice, with its unfailingly positive results, bears little relationship to the world that managers and others experience every day. This straight-line, 'do this and you'll get that' idealization is far removed from the wiggly reality. Despite this, the former continues to dominate the ways in which management is spoken about and judged in formal organizational arenas and wider society. This creates unrealistic expectations of what managers (from CEO to the front line) can sensibly achieve independently of the actions of others. Crucially, too, it distorts the ways in which they and others account formally for their actions. And so, the fantasy continues. Against this background, the book offers a radically different way of thinking about, and engaging with, the irreducible complexity of organization and management practice. Using straightforward language throughout, it sets out to help managers and others to become consciously aware of what they already know deep down about how organization works and what they - and everyone else - are actually doing in practice. It then offers a practical approach to everyday practice that takes complexity seriously. Armed with these new insights, readers will be better placed to apply their innate understanding and practical judgement to the demands that they and others face day to day. Whether these arise from their roles as managers, other practitioners, policy makers, regulatory authorities, or participants more generally.

This book presents scheduling with a medium- and short-term focus, which makes it possible to capitalize on fleeting market opportunities while simultaneously working to reconcile economic and environmental priorities. It introduces a new mixed-integer approach to hierarchical discrete-time and continuous-time scheduling, combining aspects of production and recycling, forward and reverse logistics as well as emissions trading for multi-stage supply chain networks. Problem-specific variants of relax-and-fix heuristics and genetic algorithms are also proposed. Given its scope, the book provides a range of practical tools and new perspectives for researchers and professionals in the field of supply chain management.

This textbook covers a diversity of topics in graph and network theory, both from a theoretical standpoint, and from an applied modelling point of view. Mathematica (R) is used to demonstrate much of the modelling aspects. Graph theory and model building tools are developed in tandem with effective techniques for solving practical problems via computer implementation. The book is designed with three primary readerships in mind. Individual syllabi or suggested sequences for study are provided for each of three student audiences: mathematics, applied mathematics/operations research, and computer science. In addition to the visual appeal of each page, the text contains an abundance of gems. Most chapters open with real-life problem descriptions which serve as motivation for the theoretical development of the subject matter. Each chapter concludes with three different sets of exercises. The first set of exercises are standard and geared toward the more mathematically inclined reader. Many of these are routine exercises, designed to test understanding of the material in the text, but some are more challenging. The second set of exercises is earmarked for the computer technologically savvy reader and offer computer exercises using Mathematica. The final set consists of larger projects aimed at equipping those readers with backgrounds in the applied sciences to apply the necessary skills learned in the chapter in the context of real-world problem solving. Additionally, each chapter offers biographical notes as well as pictures of graph theorists and mathematicians who have contributed significantly to the development of the results documented in the chapter. These notes are meant to bring the topics covered to life, allowing the reader to associate faces with some of the important discoveries and results presented. In total, approximately 100 biographical notes are presented throughout the book. The material in this book has been organized into three distinct parts, each with a different focus. The first part is devoted to topics in network optimization, with a focus on basic notions in algorithmic complexity and the computation of optimal paths, shortest spanning trees, maximum flows and minimum-cost flows in networks, as well as the solution of network location problems. The second part is devoted to a variety of classical problems in graph theory, including problems related to matchings, edge and vertex traversal, connectivity, planarity, edge and vertex coloring, and orientations of graphs. Finally, the focus in the third part is on modern areas of study in graph theory, covering graph domination, Ramsey theory, extremal graph theory, graph enumeration, and application of the probabilistic method.

This proceedings volume gathers together selected peer-reviewed papers presented at the second edition of the XXVI International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM), which was virtually held on February 22-24, 2021 with the main organization based at the Pontifical Catholic University of Rio de Janeiro, Brazil. Works cover a range of topics in industrial engineering, including operations and process management, global operations, managerial economics, data science and stochastic optimization, logistics and supply chain management, quality management, product development, strategy and organizational engineering, knowledge and information management, sustainability, and disaster management, to name a few. These topics broadly involve fields like operations, manufacturing, industrial and production engineering, and management. This book can be a valuable resource for researchers and practitioners in optimization research, operations research, and correlated fields.

This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.

Late one afternoon in the fall of 1976, we were sipping Sanka and speculating on the possible directions towards which research and theory in organizational science might lead. One of us had just re-read Walter Nord's Marxist critique of Human Resource Management, and the discussion evolved into an enumeration of the many articles that had appeared in the recent literature attacking the discipline, its mission, and its methods. In no time the list was long enough to suggest that a number of scholars, both young and established, were dissatisfied with the rate of progress begin made in the accumulation of knowledge about organizations. The critics we identified were located at many different schools, and they were associated with diverse research traditions and biases. The causes they identified as underlying the problems they cited varied, as did the solutions they offered. We decided to pursue these polemics with a view to seeking com monalities among them, hoping that if there were any dominant common themes, it might be possible to anticipate the directions the field could take. Our reading and thinking led us to the conclusion that many of the issues being raised by the critics of the discipline could be seen as disagreements over some implicit (or ignored) metaphysical and epistemological assumptions about organizations. We hypothesized that much of the controversy resulted from a lack of consensus regarding what organizations are and how knowledge about them can be developed."