Operational research Books

Book SynopsisPresents 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.

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Book SynopsisThis book focuses on a development of optimal, flexible, and efficient models and algorithms for cell formation in group technology. Its main aim is to provide a reliable tool that can be used by managers and engineers to design manufacturing cells based on their own preferences and constraints imposed by a particular manufacturing system.Trade Review“The book under review is a very good source … continuing the long term passion of Panos Pardalos and his collaborators in exact solution of difficult problems … . It also adds a very valuable contribution to the body of knowledge of the cell formation problem that can be used in both teaching and research including in bioinformatics.” (Boris Mirkin, Optimization Letters, 2015)Table of Contents1. The problem of cell formation.- 2. ​The p-Median problem.- 3. Application of the PMP to cell formation in group technology.- 4. The minimum multicut problem and an exact model for cell formation.- 5. Multiobjective nature of cell formation.- 6. Pattern-based heuristic for the cell formation problem in group technology.- 7. Branch-and-bound algorithm for bi-criterion cell formation problems.- 8. Summary and conclusions.- A. Solutions to the 35 CF instances from [71].- Index.- References.

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Book SynopsisWith the rise of global competitiveness among industries, it has become increasingly vital to develop novel strategies to assist in optimizing value-chain networks, thus helping to secure economic success. By employing engineer-to-order practices, many enterprises have improved their manufacturing processes.Supply Chain Strategies and the Engineer-to-Order Approach evaluates innovative processes and original operational models, frameworks, and architectures in the topic areas of industrial engineering and management science. Featuring optimized enterprise chain management strategies and emergent research within the field, this book is an essential reference source for professional, academics, and researchers specializing in enterprise operations and engineer-to-order procedures.

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Book SynopsisThe issue of sustainability has become a vital discussion in many industries within the public and private sectors. In the business realm, incorporating such practices allows organizations to re-design their operations more effectively.Green Supply Chain Management for Sustainable Business Practice examines the challenges and benefits of implementing sustainability into the core functions of contemporary enterprises, focusing on how green approaches improve operations in an ecological way. Highlighting key concepts, emerging innovations, and future directions, this book is a pivotal reference source for professionals, managers, educators, and upper-level students.

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Book SynopsisVarious industries in modern society can contribute to many different sustainable development initiatives. By implementing better processes for resource usage and its impacts, businesses can play a vital role in creating a cleaner environment.Ethics and Sustainability in Global Supply Chain Management is a comprehensive reference source for the latest scholarly material on organizational procedures and methods that ensure environmental sustainability, while maintaining effective production processes. Highlighting the most innovative topics and perspectives, such as life cycle costing, waste management, and business leadership, this book is ideally designed for professionals, academics, practitioners, graduate students, and researchers interested in developing green supply chain processes.

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Book SynopsisHeavy industrialization in the past few decades has caused several global environmental issues including poor air quality, climate change, and outdoor air pollution-related diseases. As such, consumer pressure coupled with strict governmental policies have influenced firms to adopt and implement green practices in their supply chain and business operations in order to improve socio-environmental sustainability.Global Perspectives on Green Business Administration and Sustainable Supply Chain Management is an essential reference book that discusses innovative green practices including recycling, remanufacturing, reduction in waste and adoption of renewable energy in manufacturing. It also examines environmentally friendly policies that have been adopted by many European and Western countries. Featuring coverage on a broad range of topics such as energy analysis, environmental protections, and logistics development, this book is ideally designed for managers, operations managers, executives, manufacturers, environmentalists, researchers, industry practitioners, academicians, and students.

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Book SynopsisThe world has gone through profound change since 2019, which has impacted economies, organisations, societies, and ways of working. Now, more than ever, businesses need to be prepared and resilient to large-scale changes. Written by experts, the chapters collected here address various issues such as climate change and the pandemic, suggesting ways in which future crises can be managed successfully and sharing best practice from what we have learned from recent crises. The globally diverse authorship in Corporate Resilience brings together a range of perspectives on corporate resilience and crisis management from varying industries to explore this topic in great depth. Areas studied range from building global resilience through sustainable development and social responsibility, to corporate resilience, environmental investment, internet financial reporting and reporting on human rights. Developments in Corporate Governance and Responsibility offers the latest research on topical issues international experts and has practical relevance to business managers.Table of ContentsPart 1. Building Global Resilience Chapter 1. Resilience, Dynamism and Sustainable Development: Adaptive Organisational Capability through Learning in Recurrent Crises; Dianne Bolton, Mohshin Habib, and Terry Landells Chapter 2. Social Aspects of Telework and Organisations during an Unforeseen Crisis; Ana Maria Davila Gomez and David Crowther Chapter 3. Building Resilience for a Future Organisation; Elaine Conway and Parminder Johal Chapter 4. Rethinking Sustainable Development Under Climate Change in Nigeria: A Strategic Analysis; Lukman Raimi and Fatimah Mayowa Lukman Chapter 5. Socio Cultural and Religious Drivers of Corporate Social Responsibility (CSR) in India; Amit Kumar Srivastava, Shailja Dixit, and AkanshaAbhi Srivastava Part 2. Corporate Resilience Chapter 6. A Paradigm for Examining the Interplay of Environmental Investment, Environmental Disclosure and Firm Performance in China; Ruopiao Zhang and Carlos Noronha Chapter 7. Choice of Law and Jurisdiction Uncertainties in E-contract’s Commercial Governance: A Recommendation for Mauritius; Ambareen Beebeejaun and Rajendra Parsad Gunputh Chapter 8. What Shapes Internet Financial Reporting in Africa? Exploring Firm v Country Factors; Dineshwar Ramdhony, Oren Mooneeapen, and Ajmal Bakerally Chapter 9. Effectiveness of the Lean Service Principle in controlling the Civil Service Wage Bill: A Case Study of the Government of Eswatini; Sabelo G. Sifundza and Md. Humayun Kabir Chapter 10. Towards Sustainable Prosperity for Host Communities: Appraisal of the Nigerian Petroleum Industry Act 2021; Victor Ediagbonya and Comfort Tioluwani Chapter 11. Reporting on Human Rights by Large Corporates: Interplay between Comprehensiveness and Narrative Manipulation; Leana Esterhuyse and Elda du Toit

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Book SynopsisThe proceedings of the 2017 Symposium on Chaos, Complexity and Leadership illuminate current research results and academic work from the fields of physics, mathematics, education, economics, as well as management and social sciences. The text explores chaotic and complex systems, as well as chaos and complexity theory in view of their applicability to management and leadership.This proceedings explores non-linearity as well as data-modelling and simulation in order to uncover new approaches and perspectives. Effort will not be spared in bringing theory into practice while exploring leadership and management-laden concepts. This book will cover the analysis of different chaotic developments from different fields within the concepts of chaos and complexity theory. Researchers and students in the field will find answers to questions surrounding these intertwined and compelling fields.Table of Contents

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Book SynopsisThis book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book’s closing section, several case studies are presented, helping students apply the theory covered to practical problems. The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide. Trade Review“The book is well written. The book will be of interest to mathematicians, engineers, economics and especially graduate students.” (I. M. Stancu-Minasian, zbMATH 1446.90118, 2020)Table of ContentsIntroduction.- Random Objective Functions.- Recourse Models.- Stochastic Mixed-integer Programming.- Chance Constraints.- Integrated Chance Constraints.- Assignments.- Case Studies.

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Book SynopsisThis book presents work on healthcare management and engineering using optimization and simulation methods and techniques. Specific topics covered in the contributed chapters include discrete-event simulation, patient admission scheduling, simulation-based emergency department control systems, patient transportation, cost function networks, hospital bed management, and operating theater scheduling. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.Table of ContentsA Two-Dimensional Categorization Scheme for Simulation-/Optimization-Based Decision Support in Hospitals Applied to Overall Bed Management in Interdependent Wards Under Flexibility.- Heuristics Based on the Hungarian Method for the Patient Admission Scheduling Problem.- A Bi-objective Algorithm for Robust Operating Theatre Scheduling.- Cost Function Networks to Solve Large Computational Protein Design Problems.- Modeling and Simulation in a Dialysis Center of the Hedi Chaker Hospital- Toward a Proactive and Reactive Simulation-Based Emergency Department Control System to Cope with Strain Situations.- A Decentralized Approach to the Home Healthcare Problem.- Wounded Transportation and Assignment to Hospital During Crises.- Carbon Footprints in Emergency Departments: A Simulation-Optimization Analysis.- The Effect of Risks on Discrete Event Simulation in Healthcare Systems.

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Book SynopsisThis book presents recent work that analyzes general issues of green logistics and smart cities. The contributed chapters consider operating models with important ecological, economic, and social objectives.The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.Table of ContentsThe Green-Vehicle Routing Problem: A Survey.- An Integrated Location-Inventory Routing Problem for ATMs in Banking Industry: A Green Approach.- Modelling a Future Routing Concept for Urban Air Mobility.- Putting the SC in SCORE: Solar Car Optimized Route Estimation and Smart Cities.- Evaluation and Prioritisation of Green Logistics and Transportation Practices Used in the Freight Transport Industry.- A Novel Hybrid Multi-objective Optimization Approach for Sustainable Delivery Systems with A Case Study in Izmir.- When Green Technology Meets Optimization Modelling: The Case of Routing Drones in Logistics, Agriculture and Healthcare.- Routing Electric Vehicles with Remote Servicing.

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Book SynopsisThis book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems. It is expected to be a primary reference point for researchers and doctoral students in relevant domains that seek a quick exposure to the field. The presentation focuses primarily on the applicability of the methods and the non-expert reader will find this book useful for starting designing and implementing algorithm portfolios. The book familiarizes the reader with algorithm portfolios through current advances, applications, and open problems. Fundamental issues in building effective and efficient algorithm portfolios such as selection of constituent algorithms, allocation of computational resources, interaction between algorithms and parallelism vs. sequential implementations are discussed. Several new applications are analyzed and insights on the underlying algorithmic designs are provided. Future directions, new challenges, and open problems in the design of algorithm portfolios and applications are explored to further motivate research in this field.Table of Contents1. Metaheuristic optimization algorithms.- 2. Algorithm portfolios.- 3. Selection of constituent algorithms.- 4. Allocation of computation resources.- 5. Sequential and parallel models.- 6. Recent applications.- 7. Epilogue.- References.

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Book SynopsisThis book introduces readers to benchmarking techniques in the stochastic environment, primarily stochastic data envelopment analysis (DEA), and provides stochastic models in DEA for the possibility of variations in inputs and outputs. It focuses on the application of theories and interpretations of the mathematical programs, which are combined with economic and organizational thinking. The book’s main purpose is to shed light on the advantages of the different methods in deterministic and stochastic environments and thoroughly prepare readers to properly use these methods in various cases. Simple examples, along with graphical illustrations and real-world applications in industry, are provided for a better understanding. The models introduced here can be easily used in both theoretical and real-world evaluations. This book is intended for graduate and PhD students, advanced consultants, and practitioners with an interest in quantitative performance evaluation.Table of Contents1. Benchmarking.- 2. An Introduction to Data Envelopment Analysis.- 3. Probability Theory.- 4. Stochastic Data Envelopment Analysis.- 5. Stochastic Network Data Envelopment Analysis.- 6. Stochastic Scale Elasticity.

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Book SynopsisThis 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.Table of Contents1. Demand.- 2. Supply.- 3. Market Clearing.- 4. Marginal Pricing.- 5. Market Power.- 6. Environmental Externalities.- 7. Investment.

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Book SynopsisConservation and balance laws on networks have been the subject of much research interest given their wide range of applications to real-world processes, particularly traffic flow. This open access monograph is the first to investigate different types of control problems for conservation laws that arise in the modeling of vehicular traffic. Four types of control problems are discussed - boundary, decentralized, distributed, and Lagrangian control - corresponding to, respectively, entrance points and tolls, traffic signals at junctions, variable speed limits, and the use of autonomy and communication. Because conservation laws are strictly connected to Hamilton-Jacobi equations, control of the latter is also considered. An appendix reviewing the general theory of initial-boundary value problems for balance laws is included, as well as an appendix illustrating the main concepts in the theory of conservation laws on networks. Table of ContentsIntroduction.- Boundary Control.- Decentralized Control.- Distributed Control.- Lagrangian Control.- Hamilton-Jacobi Equations.- Appendix A: Balance Laws with Boundary.- Conservation Laws on Networks.

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Book SynopsisThis is an open access book discusses readers to various methods of modeling plans and policies that address public sector issues and problems. Written for public policy and social sciences students at the upper undergraduate and graduate level, as well as public sector decision-makers, it demonstrates and compares the development and use of various deterministic and probabilistic optimization and simulation modeling methods for analyzing planning and management issues. These modeling tools offer a means of identifying and evaluating alternative plans and policies based on their physical, economic, environmental, and social impacts. Learning how to develop and use the mathematical modeling tools introduced in this book will give students useful skills when in positions of having to make informed public policy recommendations or decisions.Table of Contents1. Analyzing Public Policy Decisions.- 2. Public Sector Systems.- 3. Creating Models.- 4. Modeling Examples and Solutions.- 5. Models for Managing Money.- 6. Solving Models Using Excel.- 7. Discrete Optimization Modeling.- 8. Linear Optimization Modeling.- 9. Some Linearization Methods.- 10. Solving Models Using Calculus.- 11. Lagrangian Models.- 12. Dealing with Uncertainty.- 13. Modeling Stochastic Processes.- 14. Chance Constrained and Monte Carlo Modeling.- 15. Simulation Modeling.- 16. Multi Criteria Analyses.- 17. Fuzzy Optimization.- 18. Conclusions.

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Book SynopsisThis book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic. The book can be used as a monograph on interpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition. Table of Contents1 INTRODUCTION 1.1 Deep Learning Glossary 1.2 Evolution of Deep Learning 1.2.1 Neural Learning 1.2.2 Fuzzy Learning 1.2.3 Convergence of Fuzzy Logic and Neural Learning 1.2.4 Synergy of Neuroscience and Deep Learning 1.3 Awakening of Interpretability 1.3.1 Relevance 1.3.2 Necessity 1.3.3 The Taxonomy of Interpretability 1.4 The Question of Interpretability 1.4.1 Interpretability - Metaverse 1.4.2 Interpretability - The Right Tool 1.4.3 Interpretability - The Wrong Tool 2 NEURAL NETWORKS FOR DEEP LEARNING 2.1 Neural Network Architectures 2.1.1 Perceptron 2.1.2 Artificial Neural Network 2.1.3 Recurrent Neural Network 2.1.4 Convolutional Neural Network 2.1.5 Autoencoder Neural Network 2.1.6 Generative Adversarial Network 2.1.7 Graph Neural Network 2.2 Learning Mechanisms 2.2.1 Activation function 2.2.2 Forward Propagation 2.2.3 Backpropagation 2.2.4 Gradient Descent 2.2.5 Learning Rate 2.2.6 Optimization 2.2.7 Initialization 2.2.8 Regularization 2.3 Challenges and Limitations of Traditional Techniques 2.3.1 Resource-Demanding Checks 2.3.2 Uncertainty Measure 2.3.3 Network Learning Sanity Check 2.3.4 Gradient Checks 2.3.5 Decision Transparency 3 KNOWLEDGE ENCODING AND INTERPRETATION 3.1 What is Knowledge? 3.1.1 Image Representation 3.1.2 Word Representation 3.1.3 Graph Representation 3.2 Knowledge Encoding and Architectural Understanding 3.2.1 Role of Neurons 3.2.2 Role of Layers 3.2.3 Role of Explanation 3.2.4 Semantic Understanding 3.2.5 Network Understanding 3.3 Design and Analysis of Interpretability 3.3.1 Divide and Conquer 3.3.2 Greedy 3.3.3 Back-tracking 3.3.4 Dynamic 3.3.5 Branch and Bound 3.3.6 Brute-force 3.4 Knowledge Propagation in Deep Network Optimizers 3.4.1 Knowledge versus Performance 3.4.2 Deep versus Shallow Encoding 4 INTERPRETATION IN SPECIFIC DEEP ARCHITECTURES 4.1 Interpretation in Convolution Networks 4.1.1 Case Study: Image Representation by Unmasking Clever Hans 4.1.2 Variants of CNNs 4.1.3 Interpretation of CNNs 4.1.4 Review: CNN Visualization Techniques 4.1.5 Review: CNN Adversarial Techniques 4.1.6 Inverse Image Representation 4.1.7 Case study: Superpixels Algorithm 4.1.8 Activation Grid and Activation Map 4.1.9 Convolution Trace 4.2 Interpretation in Autoencoder Networks 4.2.1 Visualization of Latent Space 4.2.2 Sparsity and Interpretation 4.2.3 Case Study: Microscopy Structure to Structure Learning 4.3 Interpretation in Adversarial Networks 4.3.1 Interpretation in Generative Network 4.3.2 Interpretation in Latent Spaces 4.3.3 Evaluation Metrics 4.3.4 Case study: Digital Staining of Microscopy Images 4.4 Interpretation in Graph Networks 4.4.1 Neural Structured Learning 4.4.2 Graph Embedding and Interpretability 4.4.3 Evaluation Metrics for Interpretation 4.4.4 Disentangled Representation Learning on Graphs 4.4.5 Future Direction 4.5 Self-Interpretable Models 4.6 Pitfalls of Interpretability Methods 5 FUZZY DEEP LEARNING 5.1 Fuzzy Theory 5.1.1 Fuzzy Sets and Fuzzy Membership 5.1.2 Fuzzification and Defuzzification 5.1.3 Fuzzy Rules and Inference Systems 5.2 Neuro-Fuzzy Inference Systems 5.2.1 Architecture of a Neuro-Fuzzy Inference System 5.2.2 Other Design Elements of Neuro-Fuzzy Inference Systems 5.2.3 Learning mechanisms for Neuro-Fuzzy Inference Systems 5.2.4 Online Learning with Dynamic Streaming Data 5.3 Case studies 5.3.1 POPFNN Family of NFS − evolution towards sophisticated brain-like learning 5.3.2 Combining Conventional Deep Learning and Fuzzy Learning A Mathematical models and theories A.1 Choquet Integral A.1.1 Restricting the Scope of FM/ChI A.1.2 ChI Understanding from NN A.2 Deformation Invariance Property A.3 Distance Metrics A.4 Grad Weighted Class Activation Mapping A.5 Guided Saliency A.6 Jensen-Shanon Divergence A.7 Kullback-Leibler Divergence A.8 Projected Gradient Descent A.9 Pythagorean Fuzzy Number A.10 Targeted Adversarial Attack A.11 Translation Invariance Property A.12 Universal Approximation Theorem A List of digital resources and examples References .

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Book SynopsisThis book comprehensively assesses the growing importance of project data for project scheduling, risk analysis and control. It discusses the relevance of project data for both researchers and professionals, and illustrates why the collection, processing and use of such data is not as straightforward as most people think. The theme of this book is known in the literature as data-driven project management and includes the discussion of using computer algorithms, human intuition, and project data for managing projects under risk. The book reviews the basic components of data-driven project management by summarizing the current state-of-the-art methodologies, including the latest computer and machine learning algorithms and statistical methodologies, for project risk and control. It highlights the importance of artificial project data for academics, and describes the specific requirements such data must meet. In turn, the book discusses a wide variety of statistical methods available to generate these artificial data and shows how they have helped researchers to develop algorithms and tools to improve decision-making in project management. Moreover, it examines the relevance of project data from a professional standpoint and describes how professionals should collect empirical project data for better decision-making. Finally, the book introduces a new approach to data collection, generation, and analysis for creating project databases, making it relevant for academic researchers and professional project managers alike.Table of ContentsA tentative ToC is available. Please refer to the attachment.

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Book SynopsisThis book introduces solutions for sports scheduling problems in a variety of settings. In particular the book covers timetabling, the traveling tournament problem, carryover minimization, breaks minimization, tournament design, tournament planning, and referee assignment. A rich selection of applications to sports such as football, baseball, basketball, cricket or hockey are employed to illustrate the methods and techniques. In a step-by-step tutorial format the book describes the use of graph theory concepts, local search operators and integer programming in the context of sports scheduling. The methods presented in this book are essential to sports scheduling in all its dimensions, from tournaments that are followed by millions of people across the world, with broadcast rights that amount to hundreds of millions of dollars in some competitions, to amateur leagues that require coordination and logistical efforts due to the large number of tournaments and competitors.Table of ContentsLeagues, tournaments, and schedules.- Combinatorial structures.- Metaheuristics and local search.- Integer programming approaches.- Case studies.

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Book SynopsisThis third edition, which has been fully updated and now includes improved and extended explanations, is suitable as a core textbook as well as a source book for industry practitioners. It covers traditional approaches for forecasting, lot sizing, determination of safety stocks and reorder points, KANBAN policies and Material Requirements Planning. It also includes recent advances in inventory theory, for example, new techniques for multi-echelon inventory systems and Roundy's 98 percent approximation. The book also considers methods for coordinated replenishments of different items, and various practical issues in connection with industrial implementation.Other topics covered in Inventory Control include: alternative forecasting techniques, material on different stochastic demand processes and how they can be fitted to empirical data, generalized treatment of single-echelon periodic review systems, capacity constrained lot sizing, short sections on lateral transshipments and on remanufacturing, coordination and contracts. As noted, the explanations have been improved throughout the book and the text also includes problems, with solutions in an appendix.Trade Review“The book is well structured and written with care. … Numerous examples and problems to solve (given at the end of each chapter) facilitate deep understanding of the theoretical foundations and help in following the associated mathematics. A particularly attractive aspect of the presented material is its giving precise indications for the industry practitioners about application of the discussed methods and algorithms in real systems.” (Przemysław Ignaciuk, Mathematical Reviews, May, 2017)“An outstanding text in inventory control, fitting all pedagogic and scientific targets. Indispensable for researchers, doctoral students, and sophisticated practitioners and also for anybody curious and interested on the matter.” (Manuel Alberto M. Ferreira, Acta Scientia et Intellectus, Vol. 1 (3), 2015)Table of Contents

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Book SynopsisThis book explores the theoretical foundations and applications of military operational logistics (OpLog). OpLog theory has two facets: qualitative and quantitative.The qualitative facet is imbedded in the theory of operational level of war or operational art. It includes principles, imperatives and tenets, which are stated and analyzed in the first few chapters. The quantitative facet relates to the scientific aspects of OpLog. It is manifested by formal network models representing structural and operational features of an OpLog system. The book examines the two facets and integrates them into a unified presentation. Important OpLog applications a re described and discussed.Chapter 1 presents a general introduction to military logistics. Chapter 2 discusses the px;font-family: monospace;">general structure and characteristics of logistics and describes its three levels – strategic, operational and tactical. Chapter 3 describes the foundation of OpLog. Chapter 4 deals with OpLog planning. Chapter 5 addresses the issue of logistic information, and Chapter 6 deals with forecasting logistic demands. Chapters 7 and 8 are new additions to this second edition. They address logistics aspects of two contemporary operational topics – insurgencies and humanitarian assistance.Chapter 9 describes the first version of the logistic network model. Chapter 10 addresses an important OpLog characteristic – Flexibility. Chapter 11 discusses two major challenges in OpLog practice: force accumulation, 4419px; font-family: monospace;">and medical treatment and evacuation. Chapter 12 presents an inter-temporal network optimization model designed to determine deployment and employment of 3333px;font-family: monospace;">the OpLog support chain during military operations.Table of ContentsIntroduction.- Structure, Terminology and Analytic Tools.- The Foundation of Operational Logistics.- Planning.- Information.- Forecasting Logistic Demands.- Insurgency and Counterinsurgency Logistics.- Humanitarian Logistics.- The Visual Network Model.- OpLog Flexibility.- Two Critical OpLog Functions.- Optimizing Logistic Networks.

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Book SynopsisThis book treats graph colouring as an algorithmic problem, with a strong emphasis on practical applications. The author describes and analyses some of the best-known algorithms for colouring arbitrary graphs, focusing on whether these heuristics can provide optimal solutions in some cases; how they perform on graphs where the chromatic number is unknown; and whether they can produce better solutions than other algorithms for certain types of graphs, and why. The introductory chapters explain graph colouring, and bounds and constructive algorithms. The author then shows how advanced, modern techniques can be applied to classic real-world operational research problems such as seating plans, sports scheduling, and university timetabling. He includes many examples, suggestions for further reading, and historical notes, and the book is supplemented by a website with an online suite of downloadable code. The book will be of value to researchers, graduate students, and practitioners in the areas of operations research, theoretical computer science, optimization, and computational intelligence. The reader should have elementary knowledge of sets, matrices, and enumerative combinatorics.Trade Review“The book gives a comprehensive description and handling on arguably one of the most important notions of combinatorics—graph coloring. … The book is nicely written, and carries a big pile of information valuable for both users and researchers in the field.” (András Sándor Pluhár, Mathematical Reviews, February, 2017)“This well-written book will serve as a utilitarian guide to graph coloring and its practical applications. It includes many definitions, theorems, proofs, algorithms, and pointers for further reading. The book will be helpful for teaching courses on graph coloring to students of mathematics and computer science. I strongly recommend it for the intended audience.” (S. V. Nagaraj, Computing Reviews, computingreviews.com, June, 2016)“The book is a comprehensive guide to graph colouring algorithms. … The book is a nice textbook for both undergraduate and graduate students in the areas of operations research and theoretical computer science. … Finally, it is a good source of knowledge for practitioners.” (Marcin Anholcer, zbMATH 1330.05002, 2016)Table of ContentsIntroduction to Graph Colouring.- Bounds and Constructive Algorithms.- Advanced Techniques for Graph Colouring.- Algorithm Case Studies.- Applications and Extensions.- Designing Seating Plans.- Designing Sports Leagues.- Designing University Timetables.- App. A, Computing Resources.- References.- Index.

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Book SynopsisThis book describes a variety of quantitative methods that are vital to planning and control in the operations of the industrial world, from suppliers to manufacturing plants to distribution centers and to the dealers and stores. The topics include: forecasting, measuring forecast error, determining the order quantity, safety stock, when and how much inventory to replenish, all this for individual items and for a distribution network where the items are housed in multiple locations. Further quantitative methods are: manufacturing control, just-in-time, assembly, statistical process control, distribution network, supply chain management, transportation and reverse logistics. The methods are proven, practical and doable for most applications. The material in Elements of Manufacturing, Distribution and Logistics presents topics that people want and should know in the work place. The presentation is easy to read for students and practitioners. There is little need to delve into difficult mathematical relationships, and numerical examples are presented throughout to guide the reader on applications. Practitioners will be able to apply the methods learned to the systems in their locations, and the typical professional will want the book on their bookshelf for reference. Everyone in professional organizations like APICS, DSI and INFORMS; MBA graduates, people in industry, and students in management science, business and industrial engineering will find this book valuable.Table of ContentsForecasting.- Forecast Error.- Order Quantity.- Safety Stock.- Replenishments.- Distribution Control.- Manufacturing Control.- Just-in-Time.- Assembly.- Statistical Process Control.- Distribution Network.- Supply Chain Management.- Transportation.- Reverse Logistics.

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Book SynopsisThe authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.Trade Review“I would recommend this book for students in the area of operations research, but also for students and professionals from other fields (like natural sciences or social sciences) who would like not only to apply metaheuristics to solve the problems … but also to understand how they work.” (Marcin Anholcer, zbMATH 1427.90001, 2020)Table of ContentsProblems, Algorithms, Computational Complexity.- Search Space.- Tabu Search.- Simulated Annealing.- Ant Colony Optimization (ACO).- Non-PSO Optimization.- Firefly Algorithm, Cuckoo Algorithm, Lévy Flights.- Evolutionary Algorithms: Foundations.- Evolutionary Algorithms: Advanced.- Phase Transition in Optimization Problems.- Performance and Limitations of Metaheuristics.- Statistical Analysis of Research Spaces.

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Book SynopsisThis book examines issues related to the alignment of business strategies and analytics. Vast amounts of data are being generated, collected, stored, processed, analyzed, distributed and used at an ever-increasing rate by organizations. Simultaneously, managers must rapidly and thoroughly understand the factors driving their business. Business Analytics is an interactive process of analyzing and exploring enterprise data to find valuable insights that can be exploited for competitive advantage. However, to gain this advantage, organizations need to create a sophisticated analytical climate within which strategic decisions are made. As a result, there is a growing awareness that alignment among business strategies, business structures, and analytics are critical to effectively develop and deploy techniques to enhance an organization’s decision-making capability. In the past, the relevance and usefulness of academic research in the area of alignment is often questioned by practitioners, but this book seeks to bridge this gap.Aligning Business Strategies and Analytics: Bridging Between Theory and Practice is comprised of twelve chapters, divided into three sections. The book begins by introducing business analytics and the current gap between academic training and the needs within the business community. Chapters 2 - 5 examines how the use of cognitive computing improves financial advice, how technology is accelerating the growth of the financial advising industry, explores the application of advanced analytics to various facets of the industry and provides the context for analytics in practice. Chapters 6 - 9 offers real-world examples of how project management professionals tackle big-data challenges, explores the application of agile methodologies, discusses the operational benefits that can be gained by implementing real-time, and a case study on human capital analytics. Chapters 10 - 11 reviews the opportunities and potential shortfall and highlights how new media marketing and analytics fostered new insights. Finally the book concludes with a look at how data and analytics are playing a revolutionary role in strategy development in the chemical industry.Table of ContentsChapter 1: Aligning Business Strategies and Analytics: Bridging Between Theory and Practice.- Chapter 2: Cognitive Computing: Impacts on Financial Advice in Wealth Management.- Chapter 3: Living or Dying in the Mashup of American Financial Services: Literate Does Not Mean Competent.- Chapter 4: Improving Fleet Management Strategy and Operational Intelligence with Predictive Analytics.- Chapter 5: Aligning Data Analytics and Supply Chain Strategy in the Biopharmaceutical Industry.- Chapter 6: Importance of Project Management in Business Analytics: Academia and Real-world.- Chapter 7: A Review and Future Direction of Business Analytics Project Delivery.- Chapter 8: Aligning Operational Benefits of Big Data Analytics and Organizational Culture at WellSpan Health.- Chapter 9: HR Analytics: Human Capital Return on Investment, Productivity and Profit Sensitivity: A Case of Courtyard Marriott Newark at the University of Delaware.- Chapter 10: Delivering Internal Business Intelligence Services: How Different Strategies Allow Companies to Succeed by Failing Fast.- Chapter 11: Aligning Analytics with Marketing Strategy: Using Analytics to Drive Marketing Strategy with New Media Applications.- Chapter 12: Aligning Data Analytics and Strategy in the Chemical industry.

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Book SynopsisFrom the reviews: "The account is quite detailed and is written in a manner that will appeal to analysts and numerical practitioners alike...they contain everything from rigorous proofs to tables of numerical calculations.... one of the strong features of these books...that they are designed not for the expert, but for those who whish to learn the subject matter starting from little or no background...there are numerous examples, and counter-examples, to back up the theory...To my knowledge, no other authors have given such a clear geometric account of convex analysis." "This innovative text is well written, copiously illustrated, and accessible to a wide audience"Trade ReviewFrom the reviews: "The account is quite detailed and is written in a manner that will appeal to analysts and numerical practitioners alike...they contain everything from rigorous proofs to tables of numerical calculations.... one of the strong features of these books. . . [is] that they are designed not for the expert, but for those who wish to learn the subject matter starting from little or no background...there are numerous examples, and counter-examples, to back up the theory...To my knowledge, no other authors have given such a clear geometric account of convex analysis." "This innovative text is well written, copiously illustrated, and accessible to a wide audience"Table of ContentsIX. Inner Construction of the Subdifferential.- X. Conjugacy in Convex Analysis.- XI. Approximate Subdifferentials of Convex Functions.- XII. Abstract Duality for Practitioners.- XIII. Methods of ?-Descent.- XIV. Dynamic Construction of Approximate Subdifferentials: Dual Form of Bundle Methods.- XV. Acceleration of the Cutting-Plane Algorithm: Primal Forms of Bundle Methods.- Bibliographical Comments.- References.

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Book SynopsisNigel Slack is an Emeritus Professor of Operations Management and Strategy at Warwick Business School, Honorary Professor at Bath University, and 'Honorary Fellow of the European Operations Management Association'. He is an educator, consultant, and writer with a wealth of experience in many sectors. Alistair Brandon-Jones is a full-chaired Professor in Operations and Supply Chain Management and Head of the Information, Decisions, and Operations Division at the University of Bath, School of Management. He is also an Adjunct Professor for Hult International Business School and Danish Technical University. Nicola Burgess is a Reader in Operations Management at Warwick Business School. She has worked extensively with public sector organisations to understand Operations Management and Improvement in a public sector context.Table of Contents Operations management Operations performance Operations strategy Product and service innovation The structure and scope of supply Process design The layout and look of facilities Process technology People in operations Planning and control Capacity management Supply Chain Management Inventory management Planning and control systems Operations improvement Lean operations Quality management Managing risk and recovery Project management

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Book SynopsisThis 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® 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.Table of ContentsPreface.- List of Algorithms.- List of Bibliographical Notes.- Part 1. Topics in network optimisation.- 1. An introduction to graphs.- 2. Graph connectedness.- 3. Algorithmic complexity.- 4. Optimal paths.- 5. Trees.- 6. Location problems.- 7. Maximum flow networks.- 8. Minimum-cost network flows.- Part 2. Topics in classical graph theory.- 9. Matchings.- 10. Eulerian graphs.- 11. Hamiltonian graphs.- 12. Graph connectivity.- 13. Planarity.- 14. Graph colouring.- 15. Oriented graphs. Part 3. Topics in modern graph theory.- 16. Domination in graphs.- 17. Ramsey Theory.- 18. Extremal graph theory.- 19. Graph enumeration.- 20. The probabilistic method.- Index.

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Book SynopsisTable of ContentsIntroduction 1 Part 1 Artificial Intelligence Trailblazers 1 Alibaba: Using Artificial Intelligence To Power The Retail And Business-To-Business Services Of The Future 13 2 Alphabet and Google: Maximizing The Potential Of Artificial Intelligence 21 3 Amazon: Using Deep Learning To Drive Business Performance 29 4 Apple: Integrating AI Into Products And Protecting User Privacy 37 5 Baidu: Machine Learning For Search Engines And Autonomous Cars 43 6 Facebook: Using Artificial Intelligence To Improve Social Media Services 49 7 IBM: Cognitive Computing Helps Machines Debate With Humans 55 8 JD.com: Automating Retail With Artificial Intelligence 61 9 Microsoft: Making Artificial Intelligence Part Of The Fabric Of Everyday Life 69 10 Tencent: Using Artificial Intelligence To Power We Chat And Healthcare 75 Part 2 Retail, Consumer Goods and Food and Beverage Companies 11 Burberry: Using Artificial Intelligence To Sell Luxury 83 12 Coca-Cola: Using Artificial Intelligence To Stay At The Top Of The Soft Drinks Market 87 13 Domino’s: Using Artificial Intelligence To Serve Up Hundreds Of Thousands Of Pizzas Every Day 93 14 Kimberly-Clark: Using AI To Make Sense Of Customer Data 99 15 McDonald’s: Using Robots And Artificial Intelligence To Automate Processes 105 16 Samsung: Automating The Home And Workplace With Artificial Intelligence 111 17 Starbucks: Using Artificial Intelligence To Sell Millions Of Coffees Every Day 117 18 Stitch Fix: Combining The Power Of Artificial Intelligence And Humans To Disrupt Fashion Retail 123 19 Unilever: Using Artificial Intelligence To Streamline Recruiting And Onboarding 129 20 Walmart: Using Artificial Intelligence To Keep Shelves Stacked And Customers Happy 135 Part 3 Media, Entertainment and Telecom Companies 21 The Walt Disney Company: Using Artificial Intelligence To Make Magical Memories 143 22 Instagram: Using Artificial Intelligence To Tackle Online Bullying 149 23 LinkedIn: Using Artificial Intelligence To Solve The Skills Crisis 155 24 Netflix: Using Artificial Intelligence To Give Us A Better TV Experience 161 25 Press Association: Using Artificial Intelligence To Cover Local News Stories 167 26 Spotify: Using Artificial Intelligence To Find New Music You Will Love 173 27 Telefonica: Using Artificial Intelligence To Connect The Unconnected 179 28 Twitter: Using Artificial Intelligence To Fight Fake News And Spambots 185 29 Verizon: Using Machine Learning To Assess Service Quality 191 30 Viacom: Using Artificial Intelligence To Stream Videos Faster And Improve Customer Experience 197 Part 4 Services, Financial and Healthcare Companies 31 American Express: Using Artificial Intelligence To Detect Fraud And Improve Customer Experience 205 32 Elsevier: Using Artificial Intelligence To Improve Medical Decisions And Scientific Research 211 33 Entrupy: Using Artificial Intelligence To Combat The $450 Billion Counterfeit Industry 217 34 Experian: Using Artificial Intelligence To Make Mortgages Simpler 221 35 Harley-Davidson: Using Artificial Intelligence To Increase Sales 227 36 Hopper: Using Artificial Intelligence To Travel For Less 233 37 Infervision: Using Artificial Intelligence To Detect Cancer And Strokes 239 38 Mastercard: Using Artificial Intelligence To Cut Down The “False Declines” That Cost Businesses Billions Each Year 245 39 Salesforce: How Artificial Intelligence Helps Businesses Understand Their Customers 249 40 Uber: Using Artificial Intelligence To Do Everything 255 Part 5 Manufacturing, Automotive, Aerospace and Industry 4.0 Companies 41 BMW: Using Artificial Intelligence To Build And Drive The Cars Of Tomorrow 263 42 GE: Using Artificial Intelligence To Build The Internet Of Energy 269 43 John Deere: Using Artificial Intelligence To Reduce Pesticide Pollution In Agriculture 275 44 KONE: Using Artificial Intelligence To Move Millions Of People Every Day 281 45 Daimler AG: From Luxury Personal Cars To Passenger Drones 287 46 NASA: Using Artificial Intelligence To Explore Space And Distant Worlds 293 47 Shell: Using Artificial Intelligence To Tackle The Energy Transition 299 48 Siemens: Using Artificial Intelligence And Analytics To Build The Internet Of Trains 305 49 Tesla: Using Artificial Intelligence To Build Intelligent Cars 311 50 Volvo: Using Machine Learning To Build The World’s Safest Cars 317 Part 6 Final Words and Artificial Intelligence Challenges 51 Final Words And Artificial Intelligence Challenges 323 About the Author 329 Acknowledgments 331 Index 333

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Book SynopsisHiroyuki Hirano’s five pillars of the visual workplace: sort, set in order, shine, standardize and sustain are the most fundamental and often overlooked aspects in continuous improvement initiatives. Together, these concepts form the framework of the 5S System, a set of principles whose simplicity often betrays its powerful impact on the workplace.So much of the 5S System seems like common sense, that it is astonishing how often such seemingly simple practices are absent in manufacturing operations. That is why Productivity Press is proud to bring you 5S for Operators: 5 Pillars of the Visual Workplace, a hands-on book that explains the principles, rationale and implementation details of the 5S System.Easy-to-read and apply, each section of the text is loaded with questions, outlines, summaries, diagrams and illustrations. Most importantly, 5S for Operators provides the foundational knowledge that is essential for implementing not just the 5S System, but overall manufacturing improvements like shorter equipment changeovers, just-in-time inventory, total quality management and total productive maintenance. Since its publication in 1996, 5S for Operators has been and continues to be hugely popular, consistently ranking among Productivity's list of top-sellers, and its popularity is not hard to understand. 5S has proven its worth in one company after another, consistently reducing waste, guaranteeing product quality, ensuring safety and increasing the bottom line. With 5S for Operators, the 5S System can have the same profound effect on your operations. To introduce the 5S system and sell its use to executives as well as workers, consider purchasing: 5S System: An Introduction DVD (Catalog no. PP5934) Adhering to the principle of efficiency that defines this revolutionary and proven system, this video succinctly explains what is involved, who should participate, and what it will take to get started.Trade Review"I recommend this book to every supervisor who wants a commonsense, inexpensive method for improving quality, productivity, and morale within their department." Jaymie Randel, Training Coordinator, Douglas and Lomason Co. 06/01/04 This book should be read and studied by all shopfloor managers, supervisors, leaders, and associates looking for a direction to success." Steven Warywoda, Plant Manager, Douglas & Lomason Co. 06/01/04Table of Contents1. Getting Started: Chapter Overview, Purpose of this Book, What the Book is Based On, Two Ways to Use this Book, How to Get the Most Out of Your Reading , Overview of the Contents, 2. Introduction and Overview Chapter Overview, Introduction to the Five Pillars of 5S, Description of the Five Pillars, Common Types of Resistance to 5S Implementation, Benefits of 5S Implementation, 3. The First Pillar: Sort Chapter Overview, Explanation of the First Pillar: Sort, How to Sort, Steps in Red-Tagging, Accumulation of Unneeded Items, Red-Tagging Suggestions and Reminders, In Conclusion

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Book SynopsisThis state-of-the-art account unifies material developed in journal articles over the last 35 years, with two central thrusts: It describes a broad class of system models that the authors call ''stochastic processing networks'' (SPNs), which include queueing networks and bandwidth sharing networks as prominent special cases; and in that context it explains and illustrates a method for stability analysis based on fluid models. The central mathematical result is a theorem that can be paraphrased as follows: If the fluid model derived from an SPN is stable, then the SPN itself is stable. Two topics discussed in detail are (a) the derivation of fluid models by means of fluid limit analysis, and (b) stability analysis for fluid models using Lyapunov functions. With regard to applications, there are chapters devoted to max-weight and back-pressure control, proportionally fair resource allocation, data center operations, and flow management in packet networks. Geared toward researchers and grTrade Review'The deep and rich theory of stochastic processing networks has served as the analytical foundation for the study of communication networks, cloud computing systems, and manufacturing networks. This book by two of the pioneers of the theory presents an authoritative and comprehensive treatment of the topic, and will serve as an important reference to researchers in the area.' R. Srikant, University of Illinois at Urbana-Champaign'A system of interconnected resources can become overloaded and unstable even though each of its individual resources has the capacity to meet the demands on it. This striking observation, first made thirty years ago, has stimulated a major field of research. This book, written by two of the pioneers and leading researchers in the field, is a clear and authoritative account of the state-of-the-art.' Frank Kelly, University of Cambridge'This book provides an elegant and unified exposition of the general modeling framework of stochastic processing networks (SPNs) and associated theory of stability using fluid models. Much of this material was only previously available in dispersed journal articles. Adopting a continuous-time Markov chain description for SPNs, valid under fairly general assumptions on arrivals, service times and controls, enables a self-contained, accessible treatment. An array of interesting examples and extensions, especially involving applications for telecommunication and data networks, enliven the volume. This monograph will be an invaluable premier resource for graduate students and researchers in computer science, electrical and industrial engineering, applied mathematics and operations management interested in theory and applications of stochastic processing networks.' Ruth J. Williams, University of California, San DiegoTable of Contents1. Introduction; 2. Stochastic processing networks; 3. Markov representations; 4. Extensions and complements; 5. Is stability achievable?; 6. Fluid limits, fluid equations and positive recurrence; 7. Fluid equations that characterize specific policies; 8. Proving fluid model stability using Lyapunov functions; 9. Max-weight and back-pressure control; 10. Proportionally fair resource allocation; 11. Task allocation in server farms; 12. Multi-hop packet networks; Appendix A. Selected topics in real analysis; Appendix B. Selected topics in probability; Appendix C. Discrete-time Markov chains; Appendix D. Continuous-time Markov chains and phase-type distributions; Appendix E. Markovian arrival processes; Appendix F. Convergent square matrices.

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Book SynopsisPower Query is the amazing new data cleansing tool in both Excel and Power BI Desktop. Do you find yourself performing the same data cleansing steps day after day? Power Query will make it faster to clean your data the first time. While Power Query is powerful, the interface is subtle—there are tools hiding in plain sight that are easy to miss. Go beyond the obvious and take Power Query to new levels with this book.

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Book SynopsisThis book (intended for beginning analysts, students, and the people training them) bridges general business problem solving and mathematics for improved effectiveness in work and life. Full of tools for solving real-world problems, this new edition is an ideal training manual for those who are intimidated by quantitative analysis and an excellent refresher for those looking to improve the quality of their data, the clarity of their graphics, and the cogency of their arguments. In addition to numerous updates—references, URLs, and reading lists—this third edition includes revised chapters and many new and updated examples. Mastering the art of problem solving takes more than proficiency with basic calculations; it requires understanding how people use information, recognizing the importance of ideology, learning the art of storytelling, and acknowledging the important distinction between facts and values. This beginner's guide addresses these and other essential skills.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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