Computer Optimization Techniques

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Fundamentals of Optimization Techniques with Algorithms

Author : Sukanta Nayak
Publisher : Academic Press
ISBN 13 : 0128224924
Total Pages : 323 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Fundamentals of Optimization Techniques with Algorithms by : Sukanta Nayak

Download or read book Fundamentals of Optimization Techniques with Algorithms written by Sukanta Nayak and published by Academic Press. This book was released on 2020-08-25 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is a key concept in mathematics, computer science, and operations research, and is essential to the modeling of any system, playing an integral role in computer-aided design. Fundamentals of Optimization Techniques with Algorithms presents a complete package of various traditional and advanced optimization techniques along with a variety of example problems, algorithms and MATLAB© code optimization techniques, for linear and nonlinear single variable and multivariable models, as well as multi-objective and advanced optimization techniques. It presents both theoretical and numerical perspectives in a clear and approachable way. In order to help the reader apply optimization techniques in practice, the book details program codes and computer-aided designs in relation to real-world problems. Ten chapters cover, an introduction to optimization; linear programming; single variable nonlinear optimization; multivariable unconstrained nonlinear optimization; multivariable constrained nonlinear optimization; geometric programming; dynamic programming; integer programming; multi-objective optimization; and nature-inspired optimization. This book provides accessible coverage of optimization techniques, and helps the reader to apply them in practice. - Presents optimization techniques clearly, including worked-out examples, from traditional to advanced - Maps out the relations between optimization and other mathematical topics and disciplines - Provides systematic coverage of algorithms to facilitate computer coding - Gives MATLAB© codes in relation to optimization techniques and their use in computer-aided design - Presents nature-inspired optimization techniques including genetic algorithms and artificial neural networks

Computer Based Optimization Techniques

Author : Shubham Agarwal
Publisher :
ISBN 13 : 9781842659311
Total Pages : 0 pages
Book Rating : 4.6/5 (593 download)

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Book Synopsis Computer Based Optimization Techniques by : Shubham Agarwal

Download or read book Computer Based Optimization Techniques written by Shubham Agarwal and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of Operations Research, various optimization techniques and their applications, this text offers various examples and exercises in order to facilitate students in the application of concepts and analytical techniques in realistic situations.

Software Optimization for High-performance Computing

Author : Kevin R. Wadleigh
Publisher : Prentice Hall Professional
ISBN 13 : 9780130170088
Total Pages : 414 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Software Optimization for High-performance Computing by : Kevin R. Wadleigh

Download or read book Software Optimization for High-performance Computing written by Kevin R. Wadleigh and published by Prentice Hall Professional. This book was released on 2000 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The hands-on guide to high-performance coding and algorithm optimization. This hands-on guide to software optimization introduces state-of-the-art solutions for every key aspect of software performance - both code-based and algorithm-based. Two leading HP software performance experts offer comparative optimization strategies for RISC and for the new Explicitly Parallel Instruction Computing (EPIC) design used in Intel IA-64 processors. Using many practical examples, they offer specific techniques for: Predicting and measuring performance - and identifying your best optimization opportunities Storage optimization: cache, system memory, virtual memory, and I/0 Parallel processing: distributed-memory and shared-memory (SMP and ccNUMA) Compilers and loop optimization Enhancing parallelism: compiler directives, threads, and message passing Mathematical libraries and algorithms Whether you're a developer, ISV, or technical researcher, if you need to optimize high-performance software on today's leading processors, one book delivers the advanced techniques and code examples you need: Software Optimization for High Performance Computing.

Optimization Techniques in Computer Vision

Author : Mongi A. Abidi
Publisher : Springer
ISBN 13 : 3319463640
Total Pages : 295 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Optimization Techniques in Computer Vision by : Mongi A. Abidi

Download or read book Optimization Techniques in Computer Vision written by Mongi A. Abidi and published by Springer. This book was released on 2016-12-06 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems. Unconstrained optimization gives the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained optimization problems have been intensively studied, and many algorithms and tools have been developed to solve them. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc. Optimization plays a major role in a wide variety of theories for image processing and computer vision. Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision.

Optimization for Computer Vision

Author : Marco Alexander Treiber
Publisher : Springer Science & Business Media
ISBN 13 : 1447152832
Total Pages : 266 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Optimization for Computer Vision by : Marco Alexander Treiber

Download or read book Optimization for Computer Vision written by Marco Alexander Treiber and published by Springer Science & Business Media. This book was released on 2013-07-12 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical and authoritative text/reference presents a broad introduction to the optimization methods used specifically in computer vision. In order to facilitate understanding, the presentation of the methods is supplemented by simple flow charts, followed by pseudocode implementations that reveal deeper insights into their mode of operation. These discussions are further supported by examples taken from important applications in computer vision. Topics and features: provides a comprehensive overview of computer vision-related optimization; covers a range of techniques from classical iterative multidimensional optimization to cutting-edge topics of graph cuts and GPU-suited total variation-based optimization; describes in detail the optimization methods employed in computer vision applications; illuminates key concepts with clearly written and step-by-step explanations; presents detailed information on implementation, including pseudocode for most methods.

Optimization Techniques for Problem Solving in Uncertainty

Author : Tilahun, Surafel Luleseged
Publisher : IGI Global
ISBN 13 : 1522550925
Total Pages : 327 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Optimization Techniques for Problem Solving in Uncertainty by : Tilahun, Surafel Luleseged

Download or read book Optimization Techniques for Problem Solving in Uncertainty written by Tilahun, Surafel Luleseged and published by IGI Global. This book was released on 2018-06-22 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects. Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.

Optimization Techniques and Applications with Examples

Author : Xin-She Yang
Publisher : John Wiley & Sons
ISBN 13 : 1119490545
Total Pages : 384 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Optimization Techniques and Applications with Examples by : Xin-She Yang

Download or read book Optimization Techniques and Applications with Examples written by Xin-She Yang and published by John Wiley & Sons. This book was released on 2018-09-19 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.

Optimization Techniques

Author : L. R. Foulds
Publisher : Springer Science & Business Media
ISBN 13 : 1461394589
Total Pages : 512 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Optimization Techniques by : L. R. Foulds

Download or read book Optimization Techniques written by L. R. Foulds and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is the process by which the optimal solution to a problem, or optimum, is produced. The word optimum has come from the Latin word optimus, meaning best. And since the beginning of his existence Man has strived for that which is best. There has been a host of contributions, from Archimedes to the present day, scattered across many disciplines. Many of the earlier ideas, although interesting from a theoretical point of view, were originally of little practical use, as they involved a daunting amount of com putational effort. Now modern computers perform calculations, whose time was once estimated in man-years, in the figurative blink of an eye. Thus it has been worthwhile to resurrect many of these earlier methods. The advent of the computer has helped bring about the unification of optimization theory into a rapidly growing branch of applied mathematics. The major objective of this book is to provide an introduction to the main optimization tech niques which are at present in use. It has been written for final year undergrad uates or first year graduates studying mathematics, engineering, business, or the physical or social sciences. The book does not assume much mathemati cal knowledge. It has an appendix containing the necessary linear algebra and basic calculus, making it virtually self-contained. This text evolved out of the experience of teaching the material to finishing undergraduates and beginning graduates.

Simulation-Based Optimization

Author : Abhijit Gosavi
Publisher : Springer
ISBN 13 : 1489974911
Total Pages : 530 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Simulation-Based Optimization by : Abhijit Gosavi

Download or read book Simulation-Based Optimization written by Abhijit Gosavi and published by Springer. This book was released on 2014-10-30 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

Optimization Models

Author : Giuseppe C. Calafiore
Publisher : Cambridge University Press
ISBN 13 : 1107050871
Total Pages : 651 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Optimization Models by : Giuseppe C. Calafiore

Download or read book Optimization Models written by Giuseppe C. Calafiore and published by Cambridge University Press. This book was released on 2014-10-31 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems - and apply these principles to new projects.

Arithmetic Optimization Techniques for Hardware and Software Design

Author : Ryan Kastner
Publisher : Cambridge University Press
ISBN 13 : 1139487329
Total Pages : 199 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Arithmetic Optimization Techniques for Hardware and Software Design by : Ryan Kastner

Download or read book Arithmetic Optimization Techniques for Hardware and Software Design written by Ryan Kastner and published by Cambridge University Press. This book was released on 2010-05-06 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Obtain better system performance, lower energy consumption, and avoid hand-coding arithmetic functions with this concise guide to automated optimization techniques for hardware and software design. High-level compiler optimizations and high-speed architectures for implementing FIR filters are covered, which can improve performance in communications, signal processing, computer graphics, and cryptography. Clearly explained algorithms and illustrative examples throughout make it easy to understand the techniques and write software for their implementation. Background information on the synthesis of arithmetic expressions and computer arithmetic is also included, making the book ideal for newcomers to the subject. This is an invaluable resource for researchers, professionals, and graduate students working in system level design and automation, compilers, and VLSI CAD.

Advanced Memory Optimization Techniques for Low-Power Embedded Processors

Author : Manish Verma
Publisher : Springer Science & Business Media
ISBN 13 : 1402058977
Total Pages : 192 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Advanced Memory Optimization Techniques for Low-Power Embedded Processors by : Manish Verma

Download or read book Advanced Memory Optimization Techniques for Low-Power Embedded Processors written by Manish Verma and published by Springer Science & Business Media. This book was released on 2007-06-20 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes novel memory hierarchies and software optimization techniques for the optimal utilization of memory hierarchies. It presents a wide range of optimizations, progressively increasing in the complexity of analysis and of memory hierarchies. The final chapter covers optimization techniques for applications consisting of multiple processes found in most modern embedded devices.

Optimization in computer engineering – Theory and applications

Author : Zoltán Ádám Mann
Publisher : Scientific Research Publishing, Inc. USA
ISBN 13 : 1618960571
Total Pages : 182 pages
Book Rating : 4.6/5 (189 download)

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Book Synopsis Optimization in computer engineering – Theory and applications by : Zoltán Ádám Mann

Download or read book Optimization in computer engineering – Theory and applications written by Zoltán Ádám Mann and published by Scientific Research Publishing, Inc. USA. This book was released on 2011-11-15 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to provide an overview of classic as well as new research results on optimization problems and algorithms. Beside the theoretical basis, the book contains a number of chapters describing the application of the theory in practice, that is, reports on successfully solving real-world engineering challenges by means of optimization algorithms. These case studies are collected from a wide range of application domains within computer engineering. The diversity of the presented approaches offers a number of practical tips and insights into the practical application of optimization algorithms, highlighting real-world challenges and solutions. Researchers, practitioners and graduate students will find the book equally useful.

An Introduction to Optimization Techniques

Author : Vikrant Sharma
Publisher : CRC Press
ISBN 13 : 1000338231
Total Pages : 432 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis An Introduction to Optimization Techniques by : Vikrant Sharma

Download or read book An Introduction to Optimization Techniques written by Vikrant Sharma and published by CRC Press. This book was released on 2021-04-19 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Optimization Techniques introduces the basic ideas and techniques of optimization. Optimization is a precise procedure using design constraints and criteria to enable the planner to find the optimal solution. Optimization techniques have been applied in numerous fields to deal with different practical problems. This book is designed to give the reader a sense of the challenge of analyzing a given situation and formulating a model for it while explaining the assumptions and inner structure of the methods discussed as fully as possible. It includes real-world examples and applications making the book accessible to a broader readership. Features Each chapter begins with the Learning Outcomes (LO) section, which highlights the critical points of that chapter. All learning outcomes, solved examples and questions are mapped to six Bloom Taxonomy levels (BT Level). Book offers fundamental concepts of optimization without becoming too complicated. A wide range of solved examples are presented in each section after the theoretical discussion to clarify the concept of that section. A separate chapter on the application of spreadsheets to solve different optimization techniques. At the end of each chapter, a summary reinforces key ideas and helps readers recall the concepts discussed. The wide and emerging uses of optimization techniques make it essential for students and professionals. Optimization techniques have been applied in numerous fields to deal with different practical problems. This book serves as a textbook for UG and PG students of science, engineering, and management programs. It will be equally useful for Professionals, Consultants, and Managers.

Optimization of Computer Networks

Author : Pablo Pavón Mariño
Publisher : John Wiley & Sons
ISBN 13 : 1119013356
Total Pages : 399 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Optimization of Computer Networks by : Pablo Pavón Mariño

Download or read book Optimization of Computer Networks written by Pablo Pavón Mariño and published by John Wiley & Sons. This book was released on 2016-05-02 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the design and optimization of computer networks applying a rigorous optimization methodology, applicable to any network technology. It is organized into two parts. In Part 1 the reader will learn how to model network problems appearing in computer networks as optimization programs, and use optimization theory to give insights on them. Four problem types are addressed systematically – traffic routing, capacity dimensioning, congestion control and topology design. Part 2 targets the design of algorithms that solve network problems like the ones modeled in Part 1. Two main approaches are addressed – gradient-like algorithms inspiring distributed network protocols that dynamically adapt to the network, or cross-layer schemes that coordinate the cooperation among protocols; and those focusing on the design of heuristic algorithms for long term static network design and planning problems. Following a hands-on approach, the reader will have access to a large set of examples in real-life technologies like IP, wireless and optical networks. Implementations of models and algorithms will be available in the open-source Net2Plan tool from which the user will be able to see how the lessons learned take real form in algorithms, and reuse or execute them to obtain numerical solutions. An accompanying link to the author’s own Net2plan software enables readers to produce numerical solutions to a multitude of real-life problems in computer networks (www.net2plan.com).

Optimization for Machine Learning

Author : Suvrit Sra
Publisher : MIT Press
ISBN 13 : 026201646X
Total Pages : 509 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Optimization for Machine Learning by : Suvrit Sra

Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

Optimization in Industry

Author : T.A.J. Nicholson
Publisher : Routledge
ISBN 13 : 1351501429
Total Pages : 238 pages
Book Rating : 4.3/5 (515 download)

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Book Synopsis Optimization in Industry by : T.A.J. Nicholson

Download or read book Optimization in Industry written by T.A.J. Nicholson and published by Routledge. This book was released on 2017-07-12 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Teaching of optimization techniques separately from their connection with applications is pointless. This book gives a detailed exposition of the techniques. In this first volume, T. A. J. Nicholson demonstrates the full range of techniques available to the practitioner for the solution of varying problems. For each technique, the background reasoning behind its development is explained in simple terms; where helpful it is supported by a geometrical argument; and the iterative algorithm for finding the optimum is defined clearly. These steps enable the reader not only to see plainly what is happening in the method but also to reach a level of understanding necessary to write computer programs for optimization techniques. Problems are tackled in the same way--by searching a feasible region for an optimum. This approach helps the reader to develop the most essential of all skills--selecting appropriate techniques for different circumstances. The numerous worked examples in the text, supported by worked solutions, and the exercises at the end of the chapters are important aids to learning and to teachers. This book serves as an introduction to optimization techniques for students as well as a reference work for the practitioner in business and industry.