This Third Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with linear programming and then proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. You’ll discover a host of practical business applications as well as non-business applications. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered. The book’s accompanying website includes the C programs, JAVA tools, and new online instructional tools and exercises.
Dieses Buch bietet eine Einführung in angewandte Optimierungssysteme für wirtschaftswissenschaftliche Anwendungen. Es konzentriert sich methodisch auf den praxisrelevanten Bereich der linearen und gemischt-ganzzahligen Optimierung sowie auf weitere bewährte Methodiken, wie heuristische Verfahren und Simulation. Neben der Aufführung wichtiger Modelleigenschaften und Lösungsmethoden werden Techniken der Modellierung praktischer Aufgabenstellungen besprochen. Wichtige Netzwerkkmodelle, wie kürzeste Wege, Flussmodelle mit minimalen Kosten sowie Tourenplanungs- und Standortplanungsmodelle werden zusammen mit Anwendungen in der Transportlogistik für den Personen- und Güterverkehr diskutiert. Die Darstellung wird durch zahlreiche Praxisbeispiele, unter anderem aus Projekten der Autoren, abgerundet.
This book focuses largely on constrained optimization. It begins with a substantial treatment of linear programming and proceeds to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Along the way, dynamic programming and the linear complementarity problem are touched on as well. This book aims to be the first introduction to the topic. Specific examples and concrete algorithms precede more abstract topics. Nevertheless, topics covered are developed in some depth, a large number of numerical examples worked out in detail, and many recent results are included, most notably interior-point methods. The exercises at the end of each chapter both illustrate the theory, and, in some cases, extend it. Optimization is not merely an intellectual exercise: its purpose is to solve practical problems on a computer. Accordingly, the book comes with software that implements the major algorithms studied. At this point, software for the following four algorithms is available: The two-phase simplex method The primal-dual simplex method The path-following interior-point method The homogeneous self-dual methods.£/LIST£.
The principle aim of this book, entitled "Operations ResearchlManagement Science at Work", is to provide a summary snapshot of recent research in and applications of Operations Research (OR)/ Management Science (MS) in the Asia-pacific region. The book emphasises research having potential industry interest, covering a wide range of topics from major fields of ORIMS in a systematic and coherent fashion and shows the elegance of their implementations. The book is intended to serve the needs of applied researchers who are interested in applications of ORIMS algorithms. The book includes descriptions of many real-world problems together with their solutions; we hope the reader will appreciate their applicability. The Asia-pacific region has embraced business applications of decision support systems in recent years. Given that many of these applications are unaffected by legacy models or systems it has meant that state of the art ORIMS techniques have been embedded in them. Moreover, the increased use of OR/MS techniques in this region provides opportunities for identifying methodological advances that are taking place as a result of the unique nature of the applications. These also provide opportunities for exploring synergies and interfaces that exist between OR/MS, from the point of view of applications as well as theoretical advances.
Marketing models is a core component of the marketing discipline. The recent developments in marketing models have been incredibly fast with information technology (e.g., the Internet), online marketing (e-commerce) and customer relationship management (CRM) creating radical changes in the way companies interact with their customers. This has created completely new breeds of marketing models, but major progress has also taken place in existing types of marketing models. Handbook of Marketing Decision Models presents the state of the art in marketing decision models. The book deals with new modeling areas, such as customer relationship management, customer value and online marketing, as well as recent developments in other advertising, sales promotions, sales management, and competition are dealt with. New developments are in consumer decision models, models for return on marketing, marketing management support systems, and in special techniques such as time series and neural nets.
This book discusses systematically the many variations of vacation policy. The book discusses a variety of typical vacation model applications. The presentation style is unique compared with the books published in the same field – a "theorem and proof" format is used. Also, this is the first time G1/M/1 multi-server vacation models, both continuous and discrete, and the optimization and control issues have been presented in book form.
Aus dem Inhalt: Was ist Operations Research? Überblick über die Modellierungsgrundsätze des Operations Research. Einführung in die lineare Programmierung. Die Lösung linearer Programmierungsprobleme: Das Simplexverfahren. Stochastische Prozesse. Warteschlangentheorie. Lagerhaltungstheorie. Prognoseverfahren. Markov-Entscheidungsprozesse. Reliabilität. Entscheidungstheorie. Die Theorie des Simplexverfahrens Qualitätstheorie und Sensitivitätsanalyse Spezialfälle linearer Programmierungsprobleme. Die Formulierung linearer Programmierungsmodelle und Goal-Programmierung. Weitere Algorithmen der linearen Programmierung. Netzwerkanalyse einschließlich PERT-CPM. Dynamische Optimierung. Spieltheorie. Ganzzahlige Programmierung. Nichtlineare Programmierung Simulation. Anhang. Lösungen für ausgewählte Übungsaufgaben.
This book integrates the key concepts of mathematical programming and constraint programming into a unified framework that allows them to be generalized and combined. It provides a powerful, high-level modeling solution for optimization problems.
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Multiple criteria decision-making research has developed rapidly and has become a main area of research for dealing with complex decision problems which require the consideration of multiple objectives or criteria. Over the past twenty years, numerous multiple criterion decision methods have been developed which are able to solve such problems. However, the selection of an appropriate method to solve a particular decision problem is today's problem for a decision support researcher and decision-maker. Intelligent Strategies for Meta Multiple Criteria Decision-Making deals centrally with the problem of the numerous MCDM methods that can be applied to a decision problem. The book refers to this as a `meta decision problem', and it is this problem that the book analyzes. The author provides two strategies to help the decision-makers select and design an appropriate approach to a complex decision problem. Either of these strategies can be designed into a decision support system itself. One strategy is to use machine learning to design an MCDM method. This is accomplished by applying intelligent techniques, namely neural networks as a structure for approximating functions and evolutionary algorithms as universal learning methods. The other strategy is based on solving the meta decision problem interactively by selecting or designing a method suitable to the specific problem, for example, the constructing of a method from building blocks. This strategy leads to a concept of MCDM networks. Examples of this approach for a decision support system explain the possibilities of applying the elaborated techniques and their mutual interplay. The techniques outlined in the book can be used by researchers, students, and industry practitioners to better model and select appropriate methods for solving complex, multi-objective decision problems.
For over four decades, "Introduction to Operations Research" by Frederick Hillier has been the classic text on operations research. While building on the classic strengths of the text, the author continues to find new ways to make the text current and relevant to students. One way is by incorporating a wealth of state-of-the-art, user-friendly software and more coverage of business applications than ever before. The hallmark features of this edition include clear and comprehensive coverage of fundamentals, an extensive set of interesting problems and cases, and state-of-the-practice operations research software used in conjunction with examples from the text. The ninth edition introduces a new partnership with the Institute for Operations Research and Management (INFORMS). These two pillars of the OR world have come together to showcase some of the award-winning applications of operations research and integrate them with this text.
This book presents the underlying theory, model development, and applications of network Data Envelopment Analysis (DEA) in a systematic way. The field of network DEA extends and complements conventional DEA by considering not only inputs and outputs when measuring system efficiency, but also the internal structure of the system being analyzed. By analyzing the efficiency of individual internal components, and more particularly by studying the effects of relationships among components which are modeled and implemented by means of various network structures, the “network DEA” approach is able to help identify and manage the specific components that contribute inefficiencies into the overall systems. This relatively new approach comprises an important analytical tool based on mathematical programming techniques, with valuable implications to production and operations management. The existing models for measuring the efficiency of systems of specific network structures are also discussed, and the relationships between the system and component efficiencies are explored. This book should be able to inspire new research and new applications based on the current state of the art. Performance evaluation is an important task in management, and is needed to (i) better understand the past accomplishments of an organization and (ii) plan for its future development. However, this task becomes rather challenging when multiple performance metrics are involved. DEA is a powerful tool to cope with such issues. For systems or operations composed of interrelated processes, managers need to know how the performances of the various processes evaluated and how they are aggregated to form the overall performance of the system. This book provides an advanced exposition on performance evaluation of systems with network structures. It explores the network nature of most production and operation systems, and explains why network analyses are necessary.
Practical Goal Programming is intended to allow academics and practitioners to be able to build effective goal programming models, to detail the current state of the art, and to lay the foundation for its future development and continued application to new and varied fields. Suitable as both a text and reference, its nine chapters first provide a brief history, fundamental definitions, and underlying philosophies, and then detail the goal programming variants and define them algebraically. Chapter 3 details the step-by-step formulation of the basic goal programming model, and Chapter 4 explores more advanced modeling issues and highlights some recently proposed extensions. Chapter 5 then details the solution methodologies of goal programming, concentrating on computerized solution by the Excel Solver and LINGO packages for each of the three main variants, and includes a discussion of the viability of the use of specialized goal programming packages. Chapter 6 discusses the linkages between Pareto Efficiency and goal programming. Chapters 3 to 6 are supported by a set of ten exercises, and an Excel spreadsheet giving the basic solution of each example is available at an accompanying website. Chapter 7 details the current state of the art in terms of the integration of goal programming with other techniques, and the text concludes with two case studies which were chosen to demonstrate the application of goal programming in practice and to illustrate the principles developed in Chapters 1 to 7. Chapter 8 details an application in healthcare, and Chapter 9 describes applications in portfolio selection.