Here is the full list of best reference books on A First Course in Optimization.
We have put a lot of effort into researching the best books for reference on this subject and came out with a recommended list of best books. The table below contains a review of these books and 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 books; the table serves as a ready reckoner list of these best books.
|1. “Nonlinear Programming: Theory and Algorithms” by Mokhtar S Bazara and C M Shetty
Book Review: This book addresses the optimization problem of an objective function in the presence of equality and inequality constraints. The book also provides a general introduction to nonlinear programming along with demonstrative examples and guidelines for model construction. The book contains chapters on topological properties of convex sets, separation, support of convex sets, polyhedral sets, extreme points, algorithms and their convergence which involves presentation of algorithms for solving unconstrained and constrained nonlinear programming problems.
|2. “Practical Optimization” by Philip Gill and Walter Murray
Book Review: This book is of great help to the problem solvers who make the best use of optimization software. The problem solvers use existing methods to adapt and modify techniques for various problems. This book contains chapters that are very useful to solve optimization problems. The other topics are used in solving practical optimization problems.
|3. “Nonlinear Programming” by Dimitri Bertsekas
Book Review: This book focuses on nonlinear and various other types of optimization. It also contains iterative algorithms for constrained and unconstrained optimization, lagrange multipliers, large scale problems and duality, continous and discrete optimization interface. The book also provides extensive coverage of iterative optimization methods, detailed analysis of interior linear programming point methods, in depth duality theory coverage, coverage of newer topics like neural network training, discrete time optimal control and large scale optimization.
|4. “Numerical Linear Algebra and Optimization” by Philip Gill and Walter Murray and Margaret Wright|
| 5. “First Course in Optimization” by B Charles L. Byrne
“A First Course in Optimization” Book Review: This book covers the fundamentals of continuous optimization and the mathematical tools required to understand the underlying principles of optimization techniques. Spanning over 15 chapters, the text covers constrained and unconstrained optimization problems as well as issues related to linear and convex programming. It also describes basic iterative solution algorithms like gradient methods, the Newton–Raphson algorithm and its variants, and other general iterative optimization methods. Basics of advanced topics like continuous optimization and sequential unconstrained iterative optimization methods are also mentioned. This book is suitable for advanced undergraduate and graduate courses in science and engineering.
| 6. “Optimization” by Lange Kenneth Lange
“Optimization” Book Review: This book introduces optimization techniques to balance presentation of mathematical theory and development of numerical algorithms to solve finite-dimensional optimization problems. MM algorithm, block descent and ascent, convex calculus, and the calculus of variations have been treated thoroughly. Advanced topics like the Fenchel conjugate, exact penalty methods,alternating projections, projected gradient methods, subdifferentials, duality, feasibility, and Bregman iteration are also dealt in detail. Graduate students of statistics, biostatistics, applied mathematics, computational biology, computer science, economics, and physics can refer to this book to understand modern data mining techniques in high dimensions.
| 7. “Post-Optimal Analysis in Linear Semi-Infinite Optimization” by Goberna Lopez
“Post-Optimal Analysis in Linear Semi-Infinite Optimization” Book Review: This book analyzes crucial areas of linear semi-infinite optimization such as modeling uncertainty, qualitative stability analysis, quantitative stability analysis and sensitivity analysis. A comparison of the post-optimal analysis with alternative approaches to uncertain linear semi-infinite optimization (LSIO) problems is provided. Readers can choose the best way to model such problems depending on the nature and quality of the data as well as the availability of software. This work also contains open problems which readers will find intriguing a challenging. This book is intended for researchers, graduate and post-graduate students of mathematics interested in optimization, parametric optimization and related fields.
| 8. “A First Course in Combinatorial Optimization (Cambridge Texts in Applied Mathematics)” by S H Davis and Jon Lee
“A First Course in Combinatorial Optimization” Book Review: This book offers a comprehensive introduction to combinatorial optimization using matroids from the perspective of a polyhedral. Linear and integer programming, matroids and matroid optimization, shortest paths, polytopes, and network flows are some of the fundamental topics covered. Solved examples and exercises are provided, focusing on the key mathematical ideas that lead to useful models and algorithms. This book is ideal for graduate-level students of operations research, mathematics, and computer science.
| 9. “A First Course in Optimization Theory” by Rangarajan K Sundaram Sundaram Rangarajan K
“A First Course in Optimization Theory” Book Review: This book serves as a comprehensive introduction to optimization theory and its applications in economics and allied disciplines. Divided into three parts, the first part examines the existence and identification of solutions to optimization problems in Rn. The second part analyzes how solutions to optimization problems change with changes in the underlying parameters. The final part describes the fundamentals of finite- and infinite-horizon dynamic programming. Numerous examples and procedures have been provided along with detailed proofs for each result compiled. This book is suitable for first-year master’s and graduate students.
| 10. “Noisy Optimization with Evolution Strategies (Genetic Algorithms and Evolutionary Computation)” by Dirk V Arnold
“Noisy Optimization with Evolution Strategies” Book Review: This book explores evolutionary optimization in the presence of noise by investigating the performance of evolution strategies. The book systematically analyzes the effects of systematic fitness overvaluation, the benefits of distributed populations, and the potential of genetic repair for optimization in the presence of noise. The relative strength of evolution strategies is confirmed on comparing them with other direct search algorithms. The book is suitable for researchers and practitioners of evolutionary algorithms.
People who are searching for Free downloads of books and free pdf copies of these books – “Nonlinear Programming: Theory and Algorithms” by Mokhtar S Bazara and C M Shetty, “Practical Optimization” by Philip Gill and Walter Murray, “Nonlinear Programming” by Dimitri Bertsekas, “Numerical Linear Algebra and Optimization” by Philip Gill and Walter Murray and Margaret Wright, “First Course in Optimization” by B Charles L. Byrne, “Optimization” by Lange Kenneth Lange, “Post-Optimal Analysis in Linear Semi-Infinite Optimization” by Goberna Lopez, “A First Course in Combinatorial Optimization (Cambridge Texts in Applied Mathematics)” by S H Davis and Jon Lee, “A First Course in Optimization Theory” by Rangarajan K Sundaram Sundaram Rangarajan K, “Noisy Optimization with Evolution Strategies (Genetic Algorithms and Evolutionary Computation)” by Dirk V Arnold – we would like to mention that we don’t have free downloadable pdf copies of these good books and one should look for free pdf copies from these Authors only if they have explicitly made it free to download and read them.
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