This book focuses on the tactical planning level for spare parts management. It describes a series of multi-item inventory models and presents exact and heuristic optimization methods, including greedy heuristics that work well for real, life-sized problems. The intended audience consists of graduate students, starting scholars in the field of spare parts inventory control, and spare parts planning specialists in the industry. In individual chapters the authors consider topics including: a basic single-location model; single-location models with multiple machine types and/or machine groups; the multi-location model with lateral transshipments; the classical METRIC model and its generalization to multi-indenture systems; and a single-location model with an explicit modeling of the repair capacity for failed parts and the priorities that one can set there. Various chapters of the book are used in a master course at Eindhoven University of Technology and in a PhD course of the Graduate Program Operations Management and Logistics (a Dutch network that organizes PhD courses in the field of OM&L). The required pre-knowledge consists of probability theory and basic knowledge of Markov processes and queuing theory. End-of-chapter problems appear for all chapters, with some answers appearing in an appendix.

Earned Value Management (EVM) is a project management technique for measuring project progress in terms of cost, schedule and scope, and has developed into a very effective way to uncover performance problems at an early and correctible stage in any given project. From its earliest days as a financial analysis tool in the US in the early 1960 s, it steadily grew in use through the US Department of Defense until it was made the standard measurement for all DoD, NASA, and Department of Energy projects, and was widely adopted by publicly-traded companies trying to comply with the 2002 Sarbanes-Oxley ruling calling for greater transparency and accountability. It has also long been used in software engineering projects.

Winning the 2008 Research Award from IPMA for his research leading to this proposed book, author Mario Vanhoucke has surveyed the published literature to find and evaluate the effectiveness of the latest developments (and established practices) in EVM. After first explaining the fundamentals and terminology of the practice, he explores all the latest research trends and then tests them against a group of fictitious projects to gauge their effectiveness, offering general results applicable to a wide set of project types that researchers and practitioners can use to expand their work in EVM-managed projects. With a focus on the simple calculations behind EVM systems, Vanhoucke shows how they can often lead to misinterpretation and frustration and how to avoid common mistakes.

Meant to complement rather than compete with the existing books on the subject, the proposed book deals with the project performance and control phases of the project life cycle to present a detailed investigation of the project s time performance measurement methods and risk analysis techniques in order to evaluate existing and newly developed methods in terms of their abilities to improve the corrective actions decision-making process during project tracking. As readers apply what is learned from the book, EVM practices will become even more effective in project management and cost engineering. Individual chapters look at simulation studies in forecast accuracy (under nine different scenarios); schedule adherence; time sensitivity; activity sensitivity; and using top-down or bottom-up project tracking. Vanhoucke also offers an actual real-life case study, a tutorial on the use of ProTrack software (newly developed based on his research) in EVM, and conclusions on the relative effectiveness for each technique presented. This will be an important read for anyone researching, using, or studying EVM and will certainly help to push the field forward in the coming years.

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This monograph introduces a novel multiset-based conceptual, mathematical and knowledge engineering paradigm, called multigrammatical framework (MGF), used for planning and scheduling in resource-consuming, resource-producing (industrial) and resource-distributing (economical) sociotechnological systems (STS). This framework is meant to enable smart operation not only in a "business-as-usual" mode, but also in extraordinary, highly volatile or hazardous environments. It is the result of convergence and deep integration into a unified, flexible and effectively implemented formalism operating on multisets of several well-known paradigms from classical operations research and modern knowledge engineering, such as: mathematical programming, game theory, optimal scheduling, logic programming and constraint programming. The mathematical background needed for MGF, its algorithmics, applications, implementation issues, as well as its nexus with known models from operations research and theoretical computer science areas are considered. The resilience and recovery issues of an STS are studied by applying the MGF toolkit and on paying special attention to the multigrammatical assessment of resilience of energy infrastructures. MGF-represented resource-based games are introduced, and directions for further development are discussed. The author presents multiple applications to business intelligence, critical infrastructure, ecology, economy and industry. This book is addressed to scholars working in the areas of theoretical and applied computer science, artificial intelligence, systems analysis, operations research, mathematical economy and critical infrastructure protection, to engineers developing software-intensive solutions for implementation of the knowledge-based digital economy and Industry 4.0, as well as to students, aspirants and university staff. Foundational knowledge of set theory, mathematical logic and routine operations on data bases is needed to read this book. The content of the monograph is gradually presented, from simple to complex, in a well-understandable step-by-step manner. Multiple examples and accompanying figures are included in order to support the explanation of the various notions, expressions and algorithms.

This volume results from the "Second International Conference on Dynamics of Disasters" held in Kalamata, Greece, June 29-July 2, 2015. The conference covered particular topics involved in natural and man-made disasters such as war, chemical spills, and wildfires. Papers in this volume examine the finer points of disasters through: Critical infrastructure protection Resiliency Humanitarian logistic Relief supply chains Cooperative game theory Dynamical systems Decision making under risk and uncertainty Spread of diseases Contagion Funding for disaster relief Tools for emergency preparedness Response, and risk mitigation Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

'A refreshing and useful addition to the folklore of management. All in all this is a worthwhile insight into the management views and structure of some of our leading construction companies.' - J.J. Farrow, Chartered Builder This volume describes and analyses the behaviour of large UK construction firms in the determination and implementation of their strategy. It covers, in addition to the selection of objectives and the methods for their achievement, policies on growth and diversification, finance, marketing and bidding, international operations, management and labour and subcontracting. Throughout the book the relationship is examined between the theory outlined in the companion volume and the actual behaviour of firms. The final chapter concludes with a discussion of the means to bridge the gaps which are found to exist between theory and practice.

This book summarizes a series of research work on integrated process planning and scheduling (IPPS) done by the authors, focusing on discussing the properties, novel solution methods and applications of process planning, scheduling and IPPS problems under different machining environments. It is a valuable reference resource for teachers, students and researchers working in the fields of engineering, management science and other related disciplines.

This textbook provides a comprehensive overview of noncooperative and cooperative dynamic games involving uncertain parameter values, with the stochastic process being described by an event tree. Primarily intended for graduate students of economics, management science and engineering, the book is self-contained, as it defines and illustrates all relevant concepts originally introduced in static games before extending them to a dynamic framework. It subsequently addresses the sustainability of cooperative contracts over time and introduces a range of mechanisms to help avoid such agreements breaking down before reaching maturity. To illustrate the concepts discussed, the book provides various examples of how dynamic games played over event trees can be applied to environmental economics, management science, and engineering.

This book describes the latest microeconomic concepts and operations research (OR) techniques needed to comprehend the design and operation of power markets, as well as the actions of their agents: producers, consumers, operators, and regulators. This is critical when it comes to addressing a constantly evolving power system environment that incorporates an increasing number of no-marginal-cost renewable sources, increasingly competitive storage facilities, increasingly responsive demands, and widespread communication channels that allow distributed decision-making. Such evolving environments call for a re-examination of the microeconomic concepts and OR techniques required by graduate students and practitioners in the electric energy field. This accessible, tutorial-style book features numerous illustrative examples to help readers grasp the economic concepts and OR procedures used by power market professionals. The authors explian these concepts and procedures and present a vision of a renewable-dominated marketplace. Each chapter also includes exercises.

This book offers a concise introduction and comprehensive overview of the state of the art in the field of decision-making and consensus modeling, with a special emphasis on fuzzy methods. It consists of a collection of authoritative contributions reporting on the decision-making process from different perspectives: from psychology to social and political sciences, from decision sciences to data mining, and from computational sciences in general, to artificial and computational intelligence and systems. Written as a homage to Mario Fedrizzi for his scholarly achievements, creative ideas and long lasting services to different scientific communities, it introduces key theoretical concepts, describes new models and methods, and discusses a range of promising real-world applications in the field of decision-making science. It is a timely reference guide and a source of inspiration for advanced students and researchers

This era of science and engineering has attracted researchers tasked with evaluating performance and optimization of problems in the field of operations research. The book covers mathematical analysis, methods and applications involving processes such as system performance, optimization, inventory theory, reliability theory, and queueing theory. Operations Research: Methods, Techniques, and Advancements explores recent and innovative methods and advancements associated with the mathematical theory of operations research. It offers a detailed overview of mathematical modelling for general industrial systems and emphasizes the latest ideas for the benefit of society and the research community. Intended for a broad range of readers, this book is useful to academicians, industrialists, researchers, students, academia and specialists from various disciplines and those working in the industry.

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.

The focus of Supply Chain Engineering is the engineering design and planning of supply chain systems. There exists a very large variety of supply chain system types, all with different goals, constraints, and decisions, but a systematic approach for the design and planning of any supply chain can be based on the principles and methods of system engineering. In this book, author Marc Goetschalckx presents material developed at the Georgia Tech Supply Chain and Logistics Institute, the largest supply chain and logistics research and education program in the world. The book can be roughly divided into four sections. The first section focuses on data management. Since most of planning and design requires making decisions today so that supply chain functions can be executed efficiently in the future, this section introduces forecasting principles and techniques. The second section of the book focuses on transportation systems. First, the characteristics of transportation assets and infrastructure are shown. Then four chapters focus on the planning of transportation activities depending on who controls the transportation assets. The third section of the book is focused on storing goods, and the last section of the book is focused on supply chain systems that consider simultaneously procurement, production, and transportation and inventory as well as the design of the supply chain infrastructure or network design. In each chapter, first a model of the process being studied is developed followed by a description of practical solution algorithms. More advanced material is typically described in appendices. This makes it possible to use an integrated, breath-first treatment of supply chain systems by using the initial material in each chapter. A more in depth treatment of a specific topic or process can be found towards the end of each chapter. End-of-chapter exercises are included throughout. This text is suitable for several target audiences. The first target is a course for upper-level undergraduate students on supply chains. The second target is the use in a capstone senior design project in the supply chain area. The third target is an introductory course on supply chains either in a master of engineering or a master of business administration program, and the final audience consists of students attending logistics or supply chain post-graduate or continuing education courses.

The analysis and design of engineering and industrial systems has come to rely heavily on the use of optimization techniques. The theory developed over the last 40 years, coupled with an increasing number of powerful computational procedures, has made it possible to routinely solve problems arising in such diverse fields as aircraft design, material flow, curve fitting, capital expansion, and oil refining just to name a few. Mathematical programming plays a central role in each of these areas and can be considered the primary tool for systems optimization. Limits have been placed on the types of problems that can be solved, though, by the difficulty of handling functions that are not everywhere differentiable. To deal with real applications, it is often necessary to be able to optimize functions that while continuous are not differentiable in the classical sense. As the title of the book indicates, our chief concern is with (i) nondifferentiable mathematical programs, and (ii) two-level optimization problems. In the first half of the book, we study basic theory for general smooth and nonsmooth functions of many variables. After providing some background, we extend traditional (differentiable) nonlinear programming to the nondifferentiable case. The term used for the resultant problem is nondifferentiable mathematical programming. The major focus is on the derivation of optimality conditions for general nondifferentiable nonlinear programs. We introduce the concept of the generalized gradient and derive Kuhn-Tucker-type optimality conditions for the corresponding formulations.

In Risk Analysis of Complex and Uncertain Systems acknowledged risk authority Tony Cox shows all risk practitioners how Quantitative Risk Assessment (QRA) can be used to improve risk management decisions and policies. It develops and illustrates QRA methods for complex and uncertain biological, engineering, and social systems - systems that have behaviors that are just too complex to be modeled accurately in detail with high confidence - and shows how they can be applied to applications including assessing and managing risks from chemical carcinogens, antibiotic resistance, mad cow disease, terrorist attacks, and accidental or deliberate failures in telecommunications network infrastructure. This book was written for a broad range of practitioners, including decision risk analysts, operations researchers and management scientists, quantitative policy analysts, economists, health and safety risk assessors, engineers, and modelers.

Franz Ferschl is seventy. According to his birth certificate it is true, but it is unbelievable. Two of the three editors remembers very well the Golden Age of Operations Research at Bonn when Franz Ferschl worked together with Wilhelm Krelle, Martin Beckmann and Horst Albach. The importance of this fruitful cooperation is reflected by the fact that half of the contributors to this book were strongly influenced by Franz Ferschl and his colleagues at the University of Bonn. Clearly, Franz Ferschl left his traces at all the other places of his professional activities, in Vienna and Munich. This is demonstrated by the present volume as well. Born in 1929 in the Upper-Austrian Miihlviertel, his scientific education brought him to Vienna where he studied mathematics. In his early years he was attracted by Statistics and Operations Research. During his employment at the Osterreichische Bundeskammer fUr Gewerbliche Wirtschaft in Vienna he prepared his famous book on queueing theory and stochastic processes in economics. This work has been achieved during his scarce time left by his duties at the Bundeskammer, mostly between 6 a.m. and midnight. All those troubles were, however, soon rewarded by the chair of statistics at Bonn University. As a real Austrian, the amenities of the Rhineland could not prevent him from returning to Vienna, where he took the chair of statistics.

This textbook offers graduate students a concise introduction to the classic notions of convex optimization. Written in a highly accessible style and including numerous examples and illustrations, it presents everything readers need to know about convexity and convex optimization. The book introduces a systematic three-step method for doing everything, which can be summarized as "conify, work, deconify". It starts with the concept of convex sets, their primal description, constructions, topological properties and dual description, and then moves on to convex functions and the fundamental principles of convex optimization and their use in the complete analysis of convex optimization problems by means of a systematic four-step method. Lastly, it includes chapters on alternative formulations of optimality conditions and on illustrations of their use. "The author deals with the delicate subjects in a precise yet light-minded spirit... For experts in the field, this book not only offers a unifying view, but also opens a door to new discoveries in convexity and optimization...perfectly suited for classroom teaching." Shuzhong Zhang, Professor of Industrial and Systems Engineering, University of Minnesota

This volume is dedicated to Bill Helton on the occasion of his sixty fifth birthday. It contains biographical material, a list of Bill's publications, a detailed survey of Bill's contributions to operator theory, optimization and control and 19 technical articles. Most of the technical articles are expository and should serve as useful introductions to many of the areas which Bill's highly original contributions have helped to shape over the last forty odd years. These include interpolation, Szegoe limit theorems, Nehari problems, trace formulas, systems and control theory, convexity, matrix completion problems, linear matrix inequalities and optimization. The book should be useful to graduate students in mathematics and engineering, as well as to faculty and individuals seeking entry level introductions and references to the indicated topics. It can also serve as a supplementary text to numerous courses in pure and applied mathematics and engineering, as well as a source book for seminars.

Operations Research Management Science approaches have helped people for the last 40 years to understand the complex functioning of the systems based upon natural resources, as well as to manage natural resources in the most efficient manner. The areas usually viewed within the natural resources field are: agriculture, fisheries, forestry, and mining and water resources. All of these areas share the common problem of optimally allocating scarcity over a period of time. The scale of time or length of the planning horizon differs from one area to another. We have almost a continuous renewal in the case of the fisheries, periodic cycles in the case of agriculture and forestry and enormous periods of time much beyond the human perception in the case of mining resources. But in all the cases, the critical issue is to obtain an efficient use of the resource along its planned time horizon.

Another element of connection among the different natural resources is due to the interaction between the use of the resource and the environmental impact caused by its extraction or harvest. This type of interaction implies additional complexities in the underlying decision-making process, making the use of OR/MS tools especially relevant.

HANDBOOK OF OPERATIONS RESEARCH IN NATURAL RESOURCES will be the first systematic handbook treatment of quantitative modeling natural resource problems, their allocated efficient use, and societal and economic impact. AndrA(c)s Weintraub is the very top person in Natural Resource research. Moreover, he has an international reputation in OR and a former president of the International Federation of Operational Research Societies (IFORS). He has selectedco-editors who are at the top of the sub-fields in natural resources: agriculture, fisheries, forestry, and mining. The book will cover these areas in terms with contributions from researchers on modeling natural research problems, quantifying data, developing algorithms, and discussing the benefits of research implementations. The handbook will include tutorial contributions when necessary. Throughout the book, technological advances and algorithmic developments that have been driven by natural resource problems will be called out and discussed.

This book covers important issues related to managing supply chain risks from various perspectives. Supply chains today are vulnerable to disruptions with a significant impact on firms' business and performance. The aim of supply chain risk management is to identify the potential sources of risks and implement appropriate actions in order to mitigate supply chain disruptions. This book presents a set of models, frameworks, strategies, and analyses that are essential for managing supply chain risks. As a comprehensive collection of the latest research and most recent cutting-edge developments on supply chain risk and its management, the book is structured into three main parts: 1) Supply Chain Risk Management; 2) Supply Chain Vulnerability and Disruptions Management; and 3) Toward a Resilient Supply Chain. Leading academic researchers as well as practitioners have contributed chapters, combining theoretical findings and research results with a practical and contemporary view on how companies can manage the supply chain risks and disruptions, as well as how to create a resilient supply chain. This book can serve as an essential source for students and scholars who are interested in pursuing research or teaching courses in the rapidly growing area of supply chain risk management. It can also provide an interesting and informative read for managers and practitioners who need to deepen their knowledge of effective supply chain risk management.

Although chaos theory refers to the existence of between seemingly random events, it has been gaining the attention of science, technology and managements fields. The shift from traditional procedures to the dynamics of chaos and complexity theory has resulted in a new element of complexity thinking allowing for a greater capability for analysing and understanding key business processes. Chaos and Complexity Theory for Management: Nonlinear Dynamics explores the chaos and complexity theory and its relationship with the understanding of the natural chaos in the business environment. Utilising these theories would aid in comprehending the development of businesses as a complex adaptive system.

Services requiring parts has become a $1.5 trillion business annually worldwide, creating a tremendous incentive to manage the logistics of these parts efficiently by making planning and operational decisions in a rational and rigorous manner. This book provides a broad overview of modeling approaches and solution methodologies for addressing service parts inventory problems found in high-powered technology and aerospace applications. The focus in this work is on the management of high cost, low demand rate service parts found in multi-echelon settings.

This unique book, with its breadth of topics and mathematical treatment, begins by first demonstrating the optimality of an order-up-to policy [or (s-1, s)] in certain environments. This policy is used in the real world and studied throughout the text. The fundamental mathematical building blocks for modeling and solving applications of stochastic process and optimization techniques to service parts management problems are summarized extensively. A wide range of exact and approximate mathematical models of multi-echelon systems is developed and used in practice to estimate future inventory investment and part repair requirements.

The text may be used in a variety of courses for first-year graduate students or senior undergraduates, as well as for practitioners, requiring only a background in stochastic processes and optimization. It will serve as an excellent reference for key mathematical concepts and a guide to modeling a variety of multi-echelon service parts planning and operational problems.

This book is designed to assist industrial engineers and production managers in developing procedural and methodological engineering tools to meet industrial standards and mitigate engineering and production challenges. It offers practitioners expert guidance on how to implement adequate statistical process control (SPC), which takes account of the capability to ensure a stable process and then regulate if variations take place due to variables other than a random variation. Powerful engineering models of new product introduction (NPI), continuous improvement (CI), and the eight disciplines (8D) model of problem solving techniques are explained. The final three chapters introduce new methodological models in operations research (OR) and their applications in engineering, including the hyper-hybrid coordination for process effectiveness and production efficiency, and the Kraljic-Tesfay portfolio matrix of industrial buying.

Risk management has become an essential issue in supply chain management, from the modeling of the decision maker's risk preference, and the studies on uncertain elements such as demand, supply, price, lead time, etc., to the consideration of more practical background including cash flow constraints, inventory financing and delayed cash payment. In this new volume, the authors provide a framework to study the interaction of various factors related to risk and their influence on supply chain management. The scope of areas covered includes operations management, decision analysis, and business administration. This book focuses on several key issues of risk management in supply chains. Specifically, an analysis framework is presented for studying the supplier selection problem and identifying the optimal sourcing strategy in a one-retailer two-suppliers supply chain with random yields. The optimal sourcing strategy of a retailer and the pricing strategies of two suppliers under an environment of supply disruption are investigated. Besides, the authors study the dynamic inventory control problems with cash flow constraints, financing decisions as well as delayed cash payment. In addition, originating from the annual international iron ore price negotiation, the authors model the bargaining process to deal with the risk of wholesale price in the game analysis context. Within the three perspectives of risk management in supply chains, the modeling of decision maker's risk preference has been extensively studied and many results have been obtained to guide the practice. However, the analysis on the other two kinds of topics is still in its infancy, and needs more efforts from academia. It is thus the ambition and innovation for this book to contribute on risk management in supply chains in the following ways: (1) characterizing the explicit sourcing strategy (i.e., single sourcing or dual sourcing) to deal with supply disruption risk; (2) introducing the concepts of financial risk measurement by incorporating cash flow constraints, inventory financing and delayed cash payment into inventory management models; and (3) providing insights for the iron ore price negotiation to help steel manufacturers handle the risk of price increase.

This fully updated third edition is devoted to the analysis of various Stochastic Dominance (SD) decision rules. It discusses the pros and cons of each of the alternate SD rules, the application of these rules to various research areas like statistics, agriculture, medicine, measuring income inequality and the poverty level in various countries, and of course, to investment decision-making under uncertainty. The book features changes and additions to the various chapters, and also includes two completely new chapters. One deals with asymptotic SD and the relation between FSD and the maximum geometric mean (MGM) rule (or the maximum growth portfolio). The other new chapter discusses bivariate SD rules where the individual's utility is determined not only by his own wealth, but also by his standing relative to his peer group. Stochastic Dominance: Investment Decision Making under Uncertainty, 3rd Ed. covers the following basic issues: the SD approach, asymptotic SD rules, the mean-variance (MV) approach, as well as the non-expected utility approach. The non-expected utility approach focuses on Regret Theory (RT) and mainly on prospect theory (PT) and its modified version, cumulative prospect theory (CPT) which assumes S-shape preferences. In addition to these issues the book suggests a new stochastic dominance rule called the Markowitz stochastic dominance (MSD) rule corresponding to all reverse-S-shape preferences. It also discusses the concept of the multivariate expected utility and analyzed in more detail the bivariate expected utility case. From the reviews of the second edition: "This book is an economics book about stochastic dominance. ... is certainly a valuable reference for graduate students interested in decision making under uncertainty. It investigates and compares different approaches and presents many examples. Moreover, empirical studies and experimental results play an important role in this book, which makes it interesting to read." (Nicole Bauerle, Mathematical Reviews, Issue 2007 d)