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As optimization techniques have developed, a gap has arisen between the people devising the methods and the people who actually need to use them. Research into methods is necessarily long-term and located usually in academic establishments; whereas the application of an optimization technique, normally in an industrial environment, has to be justified financially in the short term. The gap is probably inevitable; but there is no need for textbooks to reflect it. Tea… More >>

Optimization in Industry: Optimization techniques

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Introduces recent advances and developments in iterative methods for solving Markovian queing and manufacturing problems, presenting future directions for research as well. Features numerous exercises and fully-worked examples. For students, practitioners and researchers in applied mathematics, scientific computing and operational research. DLC: Queing Theory. … More >>

Iterative Methods for Queuing and Manufacturing Systems

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Integer programming (discrete optimization) is best used for solving problems involving discrete, whole elements. Using integer variables, one can model logical requirements, fixed costs, sequencing and scheduling requirements, and many other problem aspects. Whether it’s taught in OR graduate programs or in math or computer science programs; in courses called “Integer Programming,” “Combinatorial Optimization,” “Combinatorial Optimization and Integer Programming”… More >>

Logic and Integer Programming

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In real-world problems related to finance, business, and management, mathematicians and economists frequently encounter optimization problems. In this classic book, George Dantzig looks at a wealth of examples and develops linear programming methods for their solutions. He begins by introducing the basic theory of linear inequalities and describes the powerful simplex method used to solve them. Treatments of the price concept, the transportation problem, and matrix … More >>

Linear Programming and Extensions

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The methodological development of integer programming has grown by leaps and bounds in the past four decades, with its main focus on linear integer programming. However, the past few years have also witnessed certain promising theoretical and methodological achievements in nonlinear integer programming. These recent developments have produced applications of nonlinear (mixed) integer programming across a variety of various areas of scientific computing, engineering,… More >>

Nonlinear Integer Programming

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Deals with the estimation of natural resources using a Monte Carlo methodology. Includes a set of tools to describe the morphological, statistical and stereological properties of spatial random models. Discusses the geostatistical simulation techniques in such a specific way. … More >>

Geostatistical Simulation: Models and Algorithms

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David Skinner shares the wealth of his experience and expertise about decision making in a clear, practical way. The additional material and insight recorded in the Third Edition reflect his own growth as a decision analysis consultant, Rice faculty member, CEO of a large consulting firm, and maturing of his thinking. This book is an excellent resource for managers, technical professionals, and decision analysts, regardless of your experience level with decision ana… More >>

Introduction to Decision Analysis

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This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
An algorithm that calculates the sensitivity to the systematic error of the fitted parameters of a least-squares regression model, with respect to the known parameters, i… More >>

Analysis of the sensitivity to the systematic error in least-squares regression models

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This is the first textbook that fully explains the neuro-dynamic programming/reinforcement learning methodology, which is a recent breakthrough in the practical application of neural networks and dynamic programming to complex problems of planning, optimal decision making, and intelligent control. Neuro-dynamic programming uses neural network approximations to overcome the “curse of dimensionality” and the “curse of modeling” that have been the bottlenecks to the… More >>

Neuro-Dynamic Programming

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The coupling of models from different physical domains and the efficient and reliable simulation of multidisciplinary problems in engineering applications are important topics for various fields of engineering, in simulation technology and in the development and analysis of numerical solvers. The volume presents advanced modelling and simulation techniques for the dynamical analysis of coupled engineering systems consisting of mechanical, electrical, hydraulic and … More >>

Simulation Techniques for Applied Dynamics

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Meta-analysis, decision analysis, and cost-effectiveness analysis are the cornerstones of evidence-based medicine. These related quantitative methods have become essential tools in the formulation of clinical and public policy based on the synthesis of evidence. All three methods are taught with increasing frequency in medical schools and schools of public health and in health policy courses at the undergraduate and graduate level. This book is a lucid introduction,… More >>

Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine

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Special features of the book 1. A very comprehensive and accessible approach in the presentation of the material. 2. A variety of solved examples to illustrate the theoretical results. 3. A large number of unsolved exercises for the students are given for practice at the end of each section. 4. Solution to each unsolved examples are given at the end of each exercise. Readership: This book is written to meet the requirements of Engineering/Science and Manageme… More >>

Optimization Techniques in Operation Research

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Biologically inspired optimization methods constitute a rapidly expanding field of research, with new applications appearing on an almost daily basis, as optimization problems of ever-increasing complexity appear in science and technology. This book provides a general introduction to such optimization methods, along with descriptions of the biological systems upon which the methods are based. The book also covers classical optimization methods, making it possible fo… More >>

Biologically Inspired Optimization Methods: An Introduction

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To perform computer simulation successfully, two rather different sets of skills are required. One of these relates to programming: a simulation program should do what its author intends and do it efficiently. The other is concerned with the collection and analysis of data: statistical tools have to be used in order to obtain with a minimum of effort, accurate and reliable estimates for the desired performance measures. Dr Mitrani covers both of these aspects of the… More >>

Simulation Techniques for Discrete Event Systems

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Mathematics is a grand subject in the way it can be applied to various problems in science and engineering. To use mathematics, one needs to understand the physical context. The author uses mathematical techniques along with observations and experiments to give an in-depth look at models for mechanical vibrations, population dynamics, and traffic flow. Equal emphasis is placed on the mathematical formulation of the problem and the interpretation of the results. In … More >>

Mathematical Models: Mechanical Vibrations, Population Dynamics, and Traffic Flow

• ISBN13: 9781880410288
• Condition: NEW
• Notes: Brand New from Publisher. No Remainder Mark.

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Is there anything more important to the success of a project than making good decisions? This skill is certainly at or near the top of the list. Yet, few of us have had formal training in decision making. Decision analysis is the discipline that helps people choose wisely under conditions of uncertainty. This book introduces risk and decision analysis applied to project management. Probability is the language of uncertainty. Fortunately, a few basic concepts i… More >>

Risk and Decision Analysis in Projects

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The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
“This text is unique in bringing together so many results hitherto found only in part in other… More >>

Markov Decision Processes: Discrete Stochastic Dynamic Programming

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This comprehensive two-volume set provides all the necessary concepts of capital investment evaluation, capital budgeting, and decision analysis. Volume 2 is specifically designed to present the concepts of decision analysis, incorporating risk and uncertainty as applied to capital investments. Mian takes the reader step-by-step through the decision-making process, providing comprehensive coverage of all decision analysis tools currently available while out… More >>

Project Economics and Decision Analysis: Probabilistic Models

Description
A rising tide lifts all ships. Understanding how to follow the tides of market momentum and take advantage of new and existing trends is one of the biggest keys of successful investing in any market. Buy high and sell low, or sell high and then buy low – if you can identify and react to market trends, you can make money either way. Use this video to master any market direction just like the pros!This product is manufactured on demand using DVD-R recordable media. Amazon…. More >>

Introduction to Trend Analysis

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Queueing Theory deals with systems where there is contention for resources, but the demands are only known probabilistically. This book can be considered to be a monograph or a textbook, and thus is aimed at two audiences: those who already know Queueing Theory but would like to know more of the Linear Algebraic Approach; and as a rst course for students who don’t already have a strong background in probability, and feel more comfortable with algebraic arguments. A… More >>

Queueing Theory: A Linear Algebraic Approach