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 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."

This book deals with World Class Operations Management (WCOM), detailing its principles, methods and organisation, and the results that this approach can bring about. Utilising real-world case studies illustrated by companies that have adopted this model (interviews with Saint-Gobain, L'Oreal, Tetra Pak, Bemis, and Bel Executives), it describes common patterns drawn from decades of hands-on experience, so as to present a theoretical approach together with the concrete application of its principles. WCOM, adopted by several multinational companies, is one of the more innovative management practises, as it integrates the best Continuous Improvement approaches (Lean, Total Productive Management, World Class Manufacturing) as well as the most innovative approaches in human dynamics like Change Leadership, Performance Behavior, Shingo Model, to name a few. Every book's chapter has been authored by an expert in these different fields, thus revealing the synergy among the different practices, which is one of the distinguishing and successful aspects of WCOM Maximising reader insights into the successful implementation of such an approach, and explaining not only its potentialities, but also its implementation dynamics, the critical points and the ways it can be integrated into different situations, this book is also about how to create a culture of excellence that is sustainable over a long period of time and delivers consistent (or ever-improving) results.

This volume is the third (III) 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 of this book (III) is on the transformation of collected information into valuable decisions and aims to shed light on how best to use digital technologies to reduce cost, inputs, and time, toward becoming more efficient and transparent. Fourteen chapters are grouped into 3 Sections. The first section of is dedicated to decisions in the value chain of agricultural products. The next section, titled Primary Production, elaborates on decision making for the improvement of processes taking place with the farm under the implementation of ICT. The last section is devoted to the development of innovative decision applications that also consider the protection of the environment, recognizing its importance in the preservation and considerate use of resources, as well as the mitigation of adverse impacts that are related to agricultural production. Planning and modeling the assessment of agricultural practices can provide farmers with valuable information prior to the execution of any task. This book provides a valuable reference for them as well as for those directly involved with decision making in planning and assessment of agricultural production. Specific advances covered in the volume: Modelling and Simulation of ICT-based agricultural systems Farm Management Information Systems (FMIS) Planning for unmanned aerial systems Agri-robotics awareness and planning Smart livestock farming Sustainable strategic planning in agri-production Food business information systems

This book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). Intended primarily as an update of the 2015 book Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis, this edited work provides an integration of applied probability and decision making. Within applied probability, it primarily includes decision analysis and reliability theory, amongst other topics closely related to risk analysis and maintenance. In decision making, it includes multicriteria decision making/aiding (MCDM/A) methods and optimization models. Within MCDM, in addition to decision analysis, some of the topics related to mathematical programming areas are considered, such as multiobjective linear programming, multiobjective nonlinear programming, game theory and negotiations, and multiobjective optimization. Methods related to these topics have been applied to the context of RRM. In MCDA, several other methods are considered, such as outranking methods, rough sets and constructive approaches. The book addresses an innovative treatment of decision making in RRM, improving the integration of fundamental concepts from both areas of RRM and decision making. This is accomplished by presenting current research developments in decision making on RRM. Some pitfalls of decision models on practical applications on RRM are discussed and new approaches for overcoming those drawbacks are presented.

Primarily an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level, the primary objective of this book is to initiate students in the art of stochastic modelling. However it is motivated by significant applications and progressively brings the student to the borders of contemporary research. Examples are from a wide range of domains, including operations research and electrical engineering. Researchers and students in these areas as well as in physics, biology and the social sciences will find this book of interest.

This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.

The development of U.S. urban transportation policy over the past half-century illustrates the changing relationships among federal, state, and local governments. This comprehensive text examines the evolution of urban transportation planning from early developments in highway planning in the 1930s to today's concerns over sustainable development, security, and pollution control. Highlighting major national events, the book examines the influence of legislation, regulations, conferences, federal programs, and advances in planning procedures and technology. The volume provides in-depth coverage of the most significant event in transportation planning, the Federal-Aid Highway Act of 1962, which created a federal mandate for a comprehensive urban transportation planning process, carried out cooperatively by states and local governments with federal funding. Claiming that urban transportation planning is more sophisticated, costly, and complex than its highway and transit planning predecessors, the book demonstrates how urban transportation planning evolved in response to changes in such factors as the environment, energy, development patterns, intergovernmental coordination, and federal transit programs. This updated, revised, and expanded edition features two new chapters on global climate change and managing under conditions of constrained resources, and covers the impact of the most recent legislation, 50 years after the Highway Act of 1962, emphasizing such timely issues as security, oil dependence, performance measurement, and public-private sector collaboration.

Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research. Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

This book offers a concise introduction to the field of financial economics and presents, for the first time, recent behavioral finance research findings that help us to understand many puzzles in traditional finance. Tailor-made for master's and PhD students, it includes tests and exercises that enable students to keep track of their progress. Parts of the book can also be used at the bachelor level.

Introduction to Management Science gives students a strong foundation in how to make decisions and solve complex problems using both quantitative methods and software tools. In addition to extensive examples, problem sets, and cases, the 13th Edition incorporates Excel 2016 and other software resources, developing students' ability to leverage the technology they will use throughout their careers. By practicing these modelling techniques, students gain a useful framework for problem-solving that they can then apply in the workplace. Samples Download the detailed table of contents Preview sample pages from Introduction to Management Science, Global Edition

With the constant evolution of change in healthcare from both a technology and governmental perspective, it is imperative to take a step back and view the big picture. Relying on hunches or beliefs is no longer sustainable, so avoid jumping to conclusions and making decisions without thoroughly understanding the statistics being analyzed. The triple aim of statistics is a conceptual model laying the foundation for improving healthcare outcomes through statistics. This foundation is: know your numbers; develop behavioral interventions; and set goals to drive change. With the availability of electronic data sources, the quantity and quality of data have grown exponentially to the point of information overload. Translating all this data into words that tell a meaningful story is overwhelming. This book takes the reader on a journey that navigates through this data to tell a story that everyone can understand and use to drive improvement. Readers will learn to tell a narrative story based on data, to develop creative, innovative and effective solutions to improve processes and outcomes utilizing the authors' tools. Topics include mortality and readmission, patient experience, patient safety survey, governmental initiatives, CMS Star Rating and Hospital Compare. Storytelling with Data in Healthcare combines methodology and statistics in the same course material, making it coherent and easier to put into practice. It uses storytelling as a tool for knowledge acquisition and retention and will be valuable for courses in nursing schools, medical schools, pharmacy schools or any healthcare profession that has a research design or statistics course offered to students. The book will be of interest to researchers, academics, healthcare professionals, and students in the fields of healthcare management and operations as well as statistics and data visualization.

Location, scheduling and design problems are assignment type problems with quadratic cost functions and occur in many contexts stretching from spatial economics via plant and office layout planning to VLSI design and similar prob lems in high-technology production settings. The presence of nonlinear inter action terms in the objective function makes these, otherwise simple, problems NP hard. In the first two chapters of this monograph we provide a survey of models of this type and give a common framework for them as Boolean quadratic problems with special ordered sets (BQPSs). Special ordered sets associated with these BQPSs are of equal cardinality and either are disjoint as in clique partitioning problems, graph partitioning problems, class-room scheduling problems, operations-scheduling problems, multi-processor assign ment problems and VLSI circuit layout design problems or have intersections with well defined joins as in asymmetric and symmetric Koopmans-Beckmann problems and quadratic assignment problems. Applications of these problems abound in diverse disciplines, such as anthropology, archeology, architecture, chemistry, computer science, economics, electronics, ergonomics, marketing, operations management, political science, statistical physics, zoology, etc. We then give a survey of the traditional solution approaches to BQPSs. It is an unfortunate fact that even after years of investigation into these problems, the state of algorithmic development is nowhere close to solving large-scale real life problems exactly. In the main part of this book we follow the polyhedral approach to combinatorial problem solving because of the dramatic algorith mic successes of researchers who have pursued this approach."

This edited volume highlights recent research advances in humanitarian relief logistics. The contributed chapters span the spectrum of key issues and activities from preparedness to mitigation operations (response), planning and execution. The volume also presents state-of-the-art methods and systems through current case studies.

Significant issues in planning and execution of humanitarian relief logistics discussed in this volume include the following:

Approaches that tackle realistic relief distribution networks. In addition to large-scale computing issues, heuristics may handle the complexity and particularities of humanitarian supply chains
Methods that integrate real-time information while effectively coping with time pressure and uncertainty, both of which are inherent to a disaster scene
Judicious recourse strategies that allow a quick and effective restoration of pre-planned solutions whenever an unpredictable event occurs
Coordination of multiple parties that are often involved in managing a disaster, including NGOs, local, state and federal agencies.

This volume provides robust evidence that research in humanitarian logistics may lead to substantial improvements in effectiveness and efficiency of disaster relief operations. This is quite encouraging, since the unique characteristics of disaster scenes provide significant opportunities for researchers to investigate novel approaches contributing to logistics research while offering a significant service to society.

This book presents various concepts and applications related to risk-conscious operations management. It also provides an overview of the risk-based engineering - fundamental to the concept of risk-conscious operations management. It presents the reliability concept to support Dependency Modelling, which includes hardware systems structures and components for reliability improvement and risk reduction. The book further develops and builds attributes and model for risk-conscious culture - critical to characterize operational approach to risk and presents human factor modelling, where it works on developing an approach for human error precursor analysis. This book will be useful for students, researchers, academicians and professionals working on identifying risk and reliability issues in complex safety and mission critical systems. It will also be beneficial for industry risk-and-reliability experts and operational safety staff working in the complex engineering systems.

The Feature-Driven Method for Structural Optimization details a novel structural optimization method within a CAD framework, integrating structural optimization and feature-based design. The book presents cutting-edge research on advanced structures and introduces the feature-driven structural optimization method by regarding engineering features as basic design primitives. Consequently, it presents a method that allows structural optimization and feature design to be done simultaneously so that feature attributes are preserved throughout the design process. The book illustrates and supports the effectiveness of the method described, showing potential applications through numerical modeling techniques and programming. This volume presents a high-performance optimization method adapted to engineering structures-a novel perspective that will help engineers in the computation, modeling and design of advanced structures.

This book has resulted from the activities of IFAC TC 5.2 "Manufacturing Modelling for Management and Control". The book offers an introduction and advanced techniques of scheduling applications to cloud manufacturing and Industry 4.0 systems for larger audience. This book uncovers fundamental principles and recent developments in the theory and application of scheduling methodology to cloud manufacturing and Industry 4.0. The purpose of this book is to present recent developments in scheduling in cloud manufacturing and Industry 4.0 and to systemize these developments in new taxonomies and methodological principles to shape this new research domain. This book addresses the needs of both researchers and practitioners to uncover the challenges and opportunities of scheduling techniques' applications to cloud manufacturing and Industry 4.0. For the first time, it comprehensively conceptualizes scheduling in cloud manufacturing and Industry 4.0 systems as a new research domain. The chapters of the book are written by the leading international experts and utilize methods of operations research, industrial engineering and computer science. Such a multi-disciplinary combination is unique and comprehensively deciphers major problem taxonomies, methodologies, and applications to scheduling in cloud manufacturing and Industry 4.0.