Description : This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems. The book’s twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja–Bretones–Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes. Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot’s stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem. The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few.
Description : This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.
Description : Economists, decision analysts, management scientists, and others have long argued that government should take a more scientific approach to decision making. Pointing to various theories for prescribing and rational izing choices, they have maintained that social goals could be achieved more effectively and at lower costs if government decisions were routinely subjected to analysis. Now, government policy makers are putting decision science to the test. Recent government actions encourage and in some cases require government decisions to be evaluated using formally defined principles 01' rationality. Will decision science pass tbis test? The answer depends on whether analysts can quickly and successfully translate their theories into practical approaches and whether these approaches promote the solution of the complex, highly uncertain, and politically sensitive problems that are of greatest concern to government decision makers. The future of decision science, perhaps even the nation's well-being, depends on the outcome. A major difficulty for the analysts who are being called upon by government to apply decision-aiding approaches is that decision science has not yet evolved a universally accepted methodology for analyzing social decisions involving risk. Numerous approaches have been proposed, including variations of cost-benefit analysis, decision analysis, and applied social welfare theory. Each of these, however, has its limitations and deficiencies and none has a proven track record for application to govern ment decisions involving risk. Cost-benefit approaches have been exten sively applied by the government, but most applications have been for decisions that were largely risk-free.
Description : Reflecting the latest developments in Microsoft Office Excel 2013, Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, 14E equips readers with a sound conceptual understanding of the role that management science plays in the decision-making process. The trusted market leader for more than two decades, the book uses a proven problem-scenario approach to introduce each quantitative technique within an applications setting. All data sets, applications, and screen visuals reflect the details of Excel 2013 to effectively prepare you to work with the latest spreadsheet tools. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Description : Provide your students with a sound conceptual understanding of the role that management science plays in the decision-making process with the latest edition of the book that has defined today's management science course: Anderson/Sweeney/Williams/Camm/Martin's AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, REVISED 13th Edition. The trusted market leader for more than two decades, the new edition of this text now reflects the latest developments in Microsoft Office Excel 2010. All data sets, applications and screen visuals throughout this REVISED 13th Edition reflect the details of Excel 2010 to accurately prepare your students to work with today's latest spreadsheet tools. The authors continue to provide unwavering accuracy with the book's proven applications-oriented approach and timely, powerful examples. The book's hallmark problem-scenario approach introduces each quantitative technique within an applications setting. Students must apply the management science model to generate solutions and recommendations for management. A comprehensive support package offers all the written and online time-saving support you need with trusted solutions written by the text authors to ensure accuracy. Students gain an understanding of today's most useful software applications with premium online content, including online chapters, LINGO software and Excel add-ins. Student even receive a copy of the popular Microsoft Project Professional 2010 on the text's accompanying CD. Trust the world leader AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, REVISED 13th Edition to provide the support your course and today's students need. The Student Essential Site PAC (Printed Access Card) that comes with the new book includes: Case Files, Example Files, Problem Files, Tutorials, Solvertable, Palisade DecisionTools (StatTools), Excel Tutorial. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Description : Enter the world of Internet of Things with the power of data science with this highly practical, engaging book About This Book Explore real-world use cases from the Internet of Things (IoT) domain using decision science with this easy-to-follow, practical book Learn to make smarter decisions on top of your IoT solutions so that your IoT is smart in a real sense This highly practical, example-rich guide fills the gap between your knowledge of data science and IoT Who This Book Is For If you have a basic programming experience with R and want to solve business use cases in IoT using decision science then this book is for you. Even if your're a non-technical manager anchoring IoT projects, you can skip the code and still benefit from the book. What You Will Learn Explore decision science with respect to IoT Get to know the end to end analytics stack – Descriptive + Inquisitive + Predictive + Prescriptive Solve problems in IoT connected assets and connected operations Design and solve real-life IoT business use cases using cutting edge machine learning techniques Synthesize and assimilate results to form the perfect story for a business Master the art of problem solving when IoT meets decision science using a variety of statistical and machine learning techniques along with hands on tasks in R In Detail With an increasing number of devices getting connected to the Internet, massive amounts of data are being generated that can be used for analysis. This book helps you to understand Internet of Things in depth and decision science, and solve business use cases. With IoT, the frequency and impact of the problem is huge. Addressing a problem with such a huge impact requires a very structured approach. The entire journey of addressing the problem by defining it, designing the solution, and executing it using decision science is articulated in this book through engaging and easy-to-understand business use cases. You will get a detailed understanding of IoT, decision science, and the art of solving a business problem in IoT through decision science. By the end of this book, you'll have an understanding of the complex aspects of decision making in IoT and will be able to take that knowledge with you onto whatever project calls for it Style and approach This scenario-based tutorial approaches the topic systematically, allowing you to build upon what you learned in previous chapters.
Description : Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.
Description : Gain a sound conceptual understanding of the role that management science plays in the decision-making process with the market leader that integrates the latest developments in Microsoft Office Excel 2016. The market-leading Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, 15E uses a proven problem-scenario approach to introduce each quantitative technique within an applications setting. All data sets, applications, and screen visuals reflect the details of Excel 2016 to effectively prepare readers to work with the latest spreadsheet tools. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.