Kindly note that we have put a lot of effort into researching the best books on Introduction To Optimization subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Introduction To Optimization" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.
|1. “Introduction to Optimum Design” by J S Arora
Book Review: This book describes a systematic approach to engineering design optimization in a very simple way. The book demonstrates many concepts and procedures with the help of many examples and illustrates their applications to many engineering design problems. The book also formulates many design problems and also contains applications of many optimization methods for structural, mechanical and industrial engineering problems. The book also contains numerous examples with detailed illustrations.
|2. “Optimization: Theory and Applications” by S S Rao
“Optimization: Theory and Applications” Book Review: This book provides a comprehensive and balanced treatment of the various optimization techniques. The development, application, and computational aspects of linear, nonlinear, geometric, dynamic, integer and stochastic programming techniques are described in the book. It also describes some classical optimization techniques. It has chapters that cover solutions of optimization problems using MATLAB, metaheuristic optimization methods, multi-objective optimization methods, and practical implementation of optimization. It offers several illustrative examples, 500 plus references in the literature of engineering optimization, and hundreds of review questions and answers.
|3. “Optimization Methods for Engineering Design” by R L Fox
“Optimization Methods for Engineering Design” Book Review: The book is mainly designed for students pursuing their graduation in engineering. It comprises chapters like introduction to optimization-based design, engineering models in optimization, models and optimization by trial-and-error, optimization with computer algorithms. It later covers specifying an optimization problem, concepts of design space. It describes how algorithms work, caution regarding optimization, modelling concepts, testing models, reducing noise, formulating intentions, and formulating constraints. The book provides several practical examples and questions with answers for readers to revise understanding.
| 4. “Biologically Inspired Optimization Methods: An Introduction” by Mattias Wahde
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“Biologically Inspired Optimization Methods: An Introduction” Book Review: The book focuses mainly on details about the advent of rapid, reliable, and cheap computing power over the past few decades and how that has transformed many. The multidisciplinary field of optimization is no exception. It describes how researchers have developed a host of new optimization algorithms that operate in a different way than the classical ones. It enables practitioners to attack optimization problems in the areas where the classical methods are either not applicable or very costly to apply. It is intended as a course book for introductory courses in stochastic optimization algorithms.
| 5. “An Introduction to Optimization” by Edwin K P Chong
“An Introduction to Optimization” Book Review: This book provides the reader with their need for accessible treatment of optimization theory and methods with an emphasis on engineering design. It gives basic definitions and notations along with the related fundamental background for linear algebra, geometry, and calculus. It represents an optimization perspective on global search methods and includes discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. It has chapters on integer programming, linear matrix inequalities, coverage on one-dimensional methods, numerous exercises at the end of the chapters along with MATLAB exercises, and drill exercises to reinforce learnings.
| 6. “Intelligent Control Systems: An Introduction with Examples” by Miklos Gerzson
“Intelligent Control Systems: An Introduction with Examples” Book Review: The book covers the rapidly developing and interdisciplinary nature of the subject. It consists of research papers on intelligent control systems and talks about the fundamentals and the general know-how in designing, implementing, and operating intelligent control systems. It discusses how intelligent control systems emerged from artificial intelligence and computer-controlled systems as an interdisciplinary field. It provides a summary of the fundamentals of knowledge representation, reasoning, real-time control systems, expert systems. The later part discusses the design, implementation, verification and operation of real-time expert systems taking G2 as an example. The material is illustrated with several examples from the field of intelligent process control.
| 7. “Introduction to Linear Optimization and Extensions with MATLAB” by Kwon
“Introduction to Linear Optimization and Extensions with MATLAB” Book Review: It is an introductory book on linear programming which discusses the important ways to mitigate parameter uncertainty. It provides a concrete and intuitive yet rigorous introduction to modern linear optimization. It discusses current linear optimization technologies such as predictor-path following interior point methods for both linear and quadratic optimization along with the inclusion of linear optimization of uncertainty like stochastic programming with recourse and robust optimization. It includes applications and case studies from finance and supply chain management that involve the use of MATLAB. It provides several examples and ends with techniques that are used to model problems with uncertainty.
| 8. “A Brief Introduction to Continuous Evolutionary Optimization” by Kramer
“A Brief Introduction to Continuous Evolutionary Optimization” Book Review: The book talks about practical optimization problems that are often hard to solve. It particularly focuses on when they are black boxes and no further information about the problem is available except the function evaluations. It introduces evolution strategies and parameter control. It introduces an adaptive penalty function for constrained optimization. It demonstrates that the meta-models reduce the number of fitness and constraint function calls for an expensive optimization problem. It describes a selection operator based on reference lines in objective space to optimize multiple conflicting objectives. Overall, the book explains the principles needed for continuous evolutionary optimization in reader-friendly language.
| 9. “Introduction To Nonlinear And Global Optimization” by Hendrix Eligius M T G
“Introduction To Nonlinear And Global Optimization” Book Review: This book is self-contained and provides a solid introduction to global and nonlinear optimization. It also provides students of mathematics and interdisciplinary sciences with a strong foundation in applied optimization techniques. It offers a unique, hands-on, and critical approach to applied optimization. It includes the presentation of numerous algorithms, examples, and illustrations to develop the required analytical skills. It is also helpful to identify optimization problems, classify the structure of a model, and to determine whether a solution fulfills optimality conditions or not. The book is a must read for students, engineers, and practitioners.
| 10. “Introduction to Computational Optimization Models for Production Planning in a Supply Chain” by David L Woodruff
“Introduction to Computational Optimization Models for Production Planning in a Supply Chain” Book Review: The book starts with an easy-to-read introduction to the concepts that are associated with the creation of optimization models for production planning. These concepts are later applied to well-known planning models, namely MRP and MRP II. Using this foundational knowledge, sophisticated models for supply chain management are developed. Another unique feature of the book is that the models are developed with an eye towards implementation. It has chapters dedicated to providing explicit examples of implementation of the basic models by means of using a variety of popular and commercially available modeling languages.
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