This book presents innovative operations research applications in business, specifically industrial engineering and its sub-disciplines. It investigates new perspectives in operations research and management science with regard to research methods, the research context, and industrial engineering, offering readers a broad range of new approaches to management problems. The book features the latest work of researchers who have worked with Professor Fusun Ulengin or built upon her work in their academic careers. Written in honor of Prof. Ulengin, this book was edited by her former Ph.D. students, who are now experts in operations research, multiple criteria decision making, competitiveness, logistics, and supply chain management. Prof. Ulengin's impact in academia is visible in the range of topics and methodologies featured in this book: Location and transportation problems, competitiveness of nations, food supply chains, debt collection, mathematical modelling, multiple criteria decision making, data envelopment analysis, random forests, and Bayesian networks.

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.

This textbook is comprised of detailed case studies covering challenging real world applications of OR techniques. Among the overall goals of the book is to provide readers with descriptions of the history and other background information on a variety of industries, service or other organizations in which decision making is an important component of their daily operations. The book considers all methods of optimum decision making in order to improve performances. It also compares possible solutions obtained by different approaches, concluding with a recommendation of the best among them for implementation. By exposing students to a variety of applications in a variety of areas and explaining how they can be modeled and solved, the book helps students develop the skills needed for modeling and solving problems that they may face in the workplace. Each chapter of "Case Studies in Operations Research: Applications of Optimal Decision Making" also includes additional data provided on the book's website on Springer.com. These files contain a brief description of the area of application, the problem and the required outputs. Also provided are links to access all the data in the problem. Finally there are project exercises for students to practice what they have learnt in the chapter, which can also be used by instructors as project assignments in their courses.

Pinedo is a major figure in the scheduling area (well versed in both stochastics and combinatorics), and knows both the academic and practitioner side of the discipline.

This book includes the integration of case studies into the text.

It will appeal to engineering and business students interested in operations research.

While many business schools are teaching Global Operations Strategy with self-made teaching materials, there are no such textbooks. Combining practical approaches with detailed theoretical underpinnings, this book provides theories, tools, frameworks, and techniques for global operations strategy, and brings real world perspectives to students and managers. Each chapter includes definition of key terms, introduction of fundamental theories, several short case examples, one long new case to explain the associated theories, and recommended further reading.

This book pulls together many perspectives on the theory, methods and practice of drawing judgments from panels of experts in assessing risks and making decisions in complex circumstances. The book is divided into four parts: Structured Expert Judgment (SEJ) current research fronts; the contributions of Roger Cooke and the Classical Model he developed; process, procedures and education; and applications. After an Introduction by the Editors, the first part presents chapters on expert elicitation of parameters of multinomial models; the advantages of using performance weighting by advancing the "random expert" hypothesis; expert elicitation for specific graphical models; modelling dependencies between experts' assessments within a Bayesian framework; preventive maintenance optimization in a Bayesian framework; eliciting life time distributions to parametrize a Dirichlet process; and on an adversarial risk analysis approach for structured expert judgment studies. The second part includes Roger Cooke's oration from 1995 on taking up his chair at Delft University of Technology; one of the editors reflections on the early decade of the Classical Model development and use; a current overview of the theory of the Classical Model, providing a deep and comprehensive perspective on its foundations and its application; and an interview with Roger Cooke. The third part starts with an interview with Professor Dame Anne Glover, who served as the Chief Scientific Advisor to the President of the European Commission. It then presents chapters on the characteristics of good elicitations by reviewing those advocated and applied; the design and development of a training course for SEJ; and on specific experiences with SEJ protocols with the intention of presenting the challenges and insights collected during these journeys. Finally, the fourth (and largest) part begins with some reflections from Willy Aspinall on his many experiences in applying the Classical Model in several application domains; it continues with related reflections on imperfect elicitations; and then it presents chapters with applications on medicines policy and management, supply chain cyber risk management, geo-political risks, terrorism and the risks facing businesses looking to internationalise.

This book is the first to approach healthcare informatics from the perspective of innovation. Drawing on the unique pairing of information and innovation, it offers an analysis to help readers rethink information technology, knowledge management, interprofessional collaboration and the generation of wisdom in the context of healthcare.The concept of "translational" research stems from the medical and health sciences, and features bidirectional and recursive information-generation processes involving bed-to-bench and bench-to-bed approaches. Based partly on this, translational systems science has become a new trend within systems sciences, motivated by the need for practical applications that help people by offering holistic systems solutions for complex ideas. Today, numerous innovations are emerging in diversified clinical practices, and there has been a remarkable convergence of new technologies in disciplines like genome therapy, immunotherapy, iPS cells, imaging diagnosis, personalized medicine, molecular targeted drugs, surgical robots, and remote nursing. Innovation is also occurring in health management fields, including health records, insurance reimbursement methods, quality control, and safety. In these areas, big data and machine learning are accelerating innovation. Behind these innovations are the creation, sharing, bridging, and translation of data, information, knowledge, and wisdom, and as such health informatics is critical in promoting health innovations.The book explores the horizons of health informatics, introducing cutting-edge practical cases and theoretical frameworks, including but not limited to fields such as big data, machine learning, drug discovery, interprofessional collaboration, electronic health records, robotics, telenursing, quality improvement, and safety.

This work prepares current and future managers and consultants focused on health care delivery systems to improve the efficiency of processes that deliver care. This material will help you manage capacity, improve patient flow, estimate process costs, and conduct experiments that lead to process improvement. Essential tools covered include process mapping and measurement, data collection and analysis, and the use of discrete event simulation as a tool for virtual experimentation and improvement. Tools are introduced with no assumption of prior training. Many examples of settings, problems, and solutions are presented, along with a generalized approach to process improvement that is specifically tailored to health care settings. Readings, exercises, and cases suitable for discussion or end-course projects are also provided. Writing is based on a decade of experience teaching at the MBA and MS levels, managing dozens of improvement processes, and a host of our prior scholarly publications, book chapters, and case studies.

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.

This volume is the last (IV) of four under the main themes of Digitizing Agriculture and Information and Communication Technologies (ICT). The four volumes cover rapidly developing processes including Sensors (I), Data (II), Decision (III), and Actions (IV). Volumes are related to 'digital transformation" within agricultural production and provision systems, and in the context of Smart Farming Technology and Knowledge-based Agriculture. Content spans broadly from data mining and visualization to big data analytics and decision making, alongside with the sustainability aspects stemming from the digital transformation of farming. The four volumes comprise the outcome of the 12th EFITA Congress, also incorporating chapters that originated from select presentations of the Congress. The focus in this volume is on the directions of Agriculture 4.0 which incorporates the transition to a new era of action in the Agricultural sector, represented by the evolution of digital technologies in 4 aspects: Big Data, Open Data, Internet of Things (IoT), and Cloud Computing. Under the heading of "Action," 14 Chapters investigate the implementation of cutting-edge technologies on real world applications. It will become apparent to the reader that the penetration of ICT in agriculture can result in several benefits related to the sustainability of the sector and to yield the maximum benefits, successful management is required. The entire discussion highlights the importance of proper education in the adoption of innovative technologies starting with the adaption of educational systems to the new era and moving to the familiarization of farmers to the new technologies. This book covers topics that relate to the digital transformation of farming. It provides examples and case studies of this transformation from around the world, examines the process of diffusion of digital technologies, and assesses the current and future sustainability aspects of digital agriculture. More specifically, it deals with issues such as: Challenges and opportunities from the transition to Agriculture 4.0 Safety and health in agricultural work automation The role of digital farming on regional-spatial planning The enrollment of Social Media in IoT-based agriculture The role of education in digital agriculture Real-life implementation cases of smart agriculture around the world

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.

This book aims to provide new research methods, theories and applications from various areas of management and engineering. In detail, the included scientific papers analyze and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of the papers delivers added value for both scholars and practitioners. Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations. To meet the needs of consumers and to promote core competences, many institutions and firms have been developing new types of services. This proceeding focus on "AI and data driven technical and management innovation in logistics, informatics and services." In detail, the included scientific papers analyze the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. This book is the documentation of the conference "11th International Conference on Logistics, Informatics and Service Sciences," which took place at the Shandong University. Due to the impact of COVID-19, LISS 2021 took place online as a virtual conference.

Implementing a food safety management system (FSMS) is a regulatory requirement for every firm in global food supply chains. At any scale, it could be influenced by many factors since the global food supply chains consist of a large number of stakeholders involved with an enormous variety of structures, the logistics of which will undoubtedly change rapidly, scale-up and diversify continuously. This book contains five chapters that aim to give an in-depth exploration of critical success factors (CSF) for food safety management in global supply chains. To fill the identified research gaps, the authors present empirical evidence from their research to verify critical success factors and their relationships with FSMS. Furthermore, the impact of supplier selection and supply chain relationships on food safety management in global supply chains are explored to identify Best Practice in FSMS implementation. This book will appeal to scholars working in food safety management, supply chain management and the impact of globalisation.

Effective logistics management has played a vital role in delivering products and services, and driving research into finding ever improving theoretical and technological solutions. While often thought of in terms of the business world, logistics and operations management strategies can also be effectively applied within the military, aeronautical, and maritime sectors. The Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations compiles interdisciplinary research on diverse issues related to logistics from an inclusive range of methodological perspectives. This publication focuses on original contributions in the form of theoretical, experimental research, and case studies on logistics strategies and operations management with an emphasis on military, aeronautical, and maritime environments. Academics and professionals operating in business environments, government institutions, and military research will find this publication beneficial to their research and professional endeavors.

OR, Defence and Security presents eleven papers, originally published in the Journal of the Operational Research Society and the Journal of Simulation, which exemplify important themes and topics in Operational Research (OR), as applied to modern-day defense and security issues. Topics range from frontline OR in a peace-support operation to new developments in combat modelling, and from the logistics of overseas intervention to defence planning at the top level. Also included are examples of applications addressing insurgency and terrorism. Edited by Dr Roger A. Forder, who had a distinguished career in OR in the UK Ministry of Defence, he has also written an authoritative introductory chapter which sets the papers in the context of the global strategic environment as it has evolved since the end of the Cold War. The OR Essentials series presents a unique cross-section of high quality research work fundamental to understanding contemporary issues and research in across a range of Operational Research (OR) topics. It brings together some of the best research papers from the esteemed Operational Research Society and its associated journals, also published by Palgrave Macmillan.

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of 'productivity analysis/data envelopment analysis' and 'data science/big data'. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others. Examples of data science techniques include linear and logistic regressions, decision trees, Naive Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubt that nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data. Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.

This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

The book shows readers exactly how to use Lean tools to design healthcare work that is smooth, efficient, error free and focused on patients and patient outcomes. It includes in-depth discussions of every important Lean tool, including value stream maps, takt time, spaghetti diagrams, workcell design, 5S, SMED, A3, Kanban, Kaizen and many more, all presented in the context of healthcare. For example, the book explains the importance of quick operating room or exam room changeovers and shows the reader specific methods for drastically reducing changeover time. Readers will learn to create healthcare value streams where workflows are based on the pull of customer/patient demand. The book also presents a variety of ways to continue improving after initial Lean successes. Methods for finding the root causes of problems and implementing effective solutions are described and demonstrated. The approach taught here is based on the Toyota Production System, which has been adopted worldwide by healthcare organizations for use in clinical, non-clinical and administrative areas.

Management of supply chains has been evolving rapidly over the last few years due to the inception of Industry 4.0, where businesses adopt automation technologies and data exchanges leading to dynamic and interconnected supply chain systems. Emphasizing on analytical approaches such as predictive and prescriptive modeling, this book presents state-of-the-art original research work dealing with advanced analytical models for the design, planning, and operation of the supply chain to provide faster and smarter decisions in the era of digitization. In particular, the book integrates machine learning and operations research models for faster and smarter decisions, presents prescriptive analytics models for strategic, tactical, and operational decision making in the supply chain, and addresses recent challenges such as sustainability in the supply chain, supply chain visibility, and supply chain digitalization. Key concepts are illustrated using real-life case studies, making the book a valuable reference for researchers, technical professionals, and students.

This book introduces readers to advanced data science techniques for signal mining in connection with agriculture. It shows how to apply heuristic modeling to improve farm-level efficiency, and how to use sensors and data intelligence to provide closed-loop feedback, while also providing recommendation techniques that yield actionable insights. The book also proposes certain macroeconomic pricing models, which data-mine macroeconomic signals and the influence of global economic trends on small-farm sustainability to provide actionable insights to farmers, helping them avoid financial disasters due to recurrent economic crises. The book is intended to equip current and future software engineering teams and operations research experts with the skills and tools they need in order to fully utilize advanced data science, artificial intelligence, heuristics, and economic models to develop software capabilities that help to achieve sustained food security for future generations.

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."