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Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.85

Presenting an approach to operations research that draws heavily on modeling as well as sensitivity analyses, this updated new edition covers the standard models of organizational decision making, emphasizing insights into problems over computing solutions.

Totally revised, this 2nd Edition includes a new chapter on decision analysis, and additional material on computer solutions of linear programming problems, LP applications, the use of sensitivity analysis output, minimal spanning tree, goal programming, network of queues, and more. Throughout, mathematics is kept to an intermediate level.

In both rich and poor nations, public resources for health care are inadequate to meet demand. Policy makers and health care providers must determine how to provide the most effective health care to citizens using the limited resources that are available. This chapter describes current and future challenges in the delivery of health care, and outlines the role that operations research (OR) models can play in helping to solve those problems. The chapter concludes with an overview of this book – its intended audience, the areas covered, and a description of the subsequent chapters. KEY WORDS Health care delivery, Health care planning HEALTH CARE DELIVERY: PROBLEMS AND CHALLENGES 3 1.1 WORLDWIDE HEALTH: THE PAST 50 YEARS Human health has improved significantly in the last 50 years. In 1950, global life expectancy was 46 years [1]. That figure rose to 61 years by 1980 and to 67 years by 1998 [2]. Much of these gains occurred in low- and middle-income countries, and were due in large part to improved nutrition and sanitation, medical innovations, and improvements in public health infrastructure.

This text provides a technical exploration of military and commercial test and evaluation. Chapter One provides important history, and addresses the vital relationship of quality test and evaluation (T&E) to the acquisition and operations of defence weapons systems. Subsequent chapters cover such concepts as cost and operational effectiveness analysis, modelling and simulation, and verification, validation, and accreditation, among others. In the closing chapters, concepts for the future are discussed.

Significantly revised, this book provides balanced coverage of the theory, applications, and computations of operations research. The applications and computations in operations research are emphasized. Significantly revised, this text streamlines the coverage of the theory, applications, and computations of operations research. Numerical examples are effectively used to explain complex mathematical concepts. A separate chapter of fully analyzed applications aptly demonstrates the diverse use of OR. The popular commercial and tutorial software AMPL, Excel, Excel Solver, and Tora are used throughout the book to solve practical problems and to test theoretical concepts. New materials include Markov chains, TSP heuristics, new LP models, and a totally new simplex-based approach to LP sensitivity analysis.

Operations Research: An Introduction, 9/e is ideal for or junior/senior undergraduate and first-year graduate courses in Operations Research in departments of Industrial Engineering, Business Administration, Statistics, Computer Science, and Mathematics.   This text streamlines the coverage of the theory, applications, and computations of operations research. Numerical examples are effectively used to explain complex mathematical concepts. A separate chapter of fully analyzed applications aptly demonstrates the diverse use of OR. The popular commercial and tutorial software AMPL, Excel, Excel Solver, and Tora are used throughout the book to solve practical problems and to test theoretical concepts.

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Students with diverse backgrounds will face a multitude of decisions in a variety of engineering, scientific, industrial, and financial settings. They will need to know how to identify problems that the methods of operations research (OR) can solve, how to structure the problems into standard mathematical models, and finally how to apply or develop computational tools to solve the problems.Perfect for any one-semester course in OR, Operations Research: A Practical Introduction answers all of these needs. In addition to providing a practical introduction and guide to using OR techniques, it includes a timely examination of innovative methods and practical issues related to the development and use of computer implementations. It provides a sound introduction to the mathematical models relevant to OR and illustrates the effective use of OR techniques with examples drawn from industrial, computing, engineering, and business applicationsMany students will take only one course in the techniques of Operations Research. Operations Research: A Practical Introduction offers them the greatest benefit from that course through a broad survey of the techniques and tools available for quantitative decision making. It will also encourage other students to pursue more advanced studies and provides you a concise, well-structured, vehicle for delivering the best possible overview of the discipline.

Discusses basic concepts and methods associated with the application of operations research toward arriving at an optimum mix, level, or choice.

In a rapidly developing field like Operations Research, its easy to get overwhelmed by the variety of topics and analytic techniques. Paul Jensen and Jonathan Bard help you master the expensive field by focusing on the fundamental models and methodologies underlying the practice of Operations Research. Bridging the gap between theory and practice, the author presents the quantitative tools and models most important to understanding modern operations research. You'll come to appreciate the power of OR techniques in solving real-world problems and applications in your own field. You'll learn how to translate complex situations into mathematical models, solve models and turn models into solutions. This text is designed to bridge the gap between theory and practice by presenting the quantitative tools and models most suited for modern operations research. The principal goal is to give analysts, engineers, and decision makers a larger appreciation of their roles by defining a common terminology and by explaining the interfaces between the underlying methodologies. Features Divides each subject into methods and models, giving you greater flexibility in how you approach the material. Concise and focused presentation highlights central ideas. Many examples throughout the text will help you better understand mathematical material.

New! This book is in the same immaculate condition as when it was published 1.74

Students with diverse backgrounds will face a multitude of decisions in a variety of engineering, scientific, industrial, and financial settings. They will need to know how to identify problems that the methods of operations research (OR) can solve, how to structure the problems into standard mathematical models, and finally how to apply or develop computational tools to solve the problems.Perfect for any one-semester course in OR, Operations Research: A Practical Introduction answers all of these needs. In addition to providing a practical introduction and guide to using OR techniques, it includes a timely examination of innovative methods and practical issues related to the development and use of computer implementations. It provides a sound introduction to the mathematical models relevant to OR and illustrates the effective use of OR techniques with examples drawn from industrial, computing, engineering, and business applicationsMany students will take only one course in the techniques of Operations Research. Operations Research: A Practical Introduction offers them the greatest benefit from that course through a broad survey of the techniques and tools available for quantitative decision making. It will also encourage other students to pursue more advanced studies and provides you a concise, well-structured, vehicle for delivering the best possible overview of the discipline.

This best-selling introduction to operations research now features the Windows versions of LINDO and LINGO. (LINDO, GINO, and LINGO software packages are also available with the book in Macintosh or DOS versions). Forward thinking in approach, this book emphasizes model-formulation and model-building skills. Winston includes material for a three-semester course, organized into self-contained units that provide flexibility in selecting material. Requiring a background in calculus, linear algebra, and statistics, OPERATIONS RESEARCH offers comprehensive coverage for applications-oriented courses in linear or mathematical programming and stochastic and probabilistic models and processes at the undergraduate and graduate level.

This best-selling introduction to operations research now features the Windows versions of LINDO and LINGO. (LINDO, GINO, and LINGO software packages are also available with the book in Macintosh or DOS versions). Forward thinking in approach, this book emphasizes model-formulation and model-building skills. Winston includes material for a three-semester course, organized into self-contained units that provide flexibility in selecting material. Requiring a background in calculus, linear algebra, and statistics, OPERATIONS RESEARCH offers comprehensive coverage for applications-oriented courses in linear or mathematical programming and stochastic and probabilistic models and processes at the undergraduate and graduate level.

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The objective of this book is to provide a valuable compendium of problems as a reference for undergraduate and graduate students, faculty, researchers and practitioners of operations research and management science. These problems can serve as a basis for the development or study of assignments and exams. Also, they can be useful as a guide for the first stage of the model formulation, i.e. the definition of a problem. The book is divided into 11 chapters that address the following topics: Linear programming, integer programming, non linear programming, network modeling, inventory theory, queue theory, tree decision, game theory, dynamic programming and markov processes. Readers are going to find a considerable number of statements of operations research applications for management decision-making. The solutions of these problems are provided in a concise way although all topics start with a more developed resolution. The proposed problems are based on the research experience of the authors in real-world companies so much as on the teaching experience of the authors in order to develop exam problems for industrial engineering and business administration studies.

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This book offers a compendium of problems in operations research, in such areas as linear programming, integer programming, non-linear programming, network modeling, inventory theory, queue theory, tree decision, dynamic programming, Markov processes and more.