Computational Optimization Techniques And Applications
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Computational Optimization Techniques and Applications
Author: Muhammad Sarfraz
language: en
Publisher: BoD – Books on Demand
Release Date: 2021-08-25
Computational optimization is an active and important area of study, practice, and research today. It covers a wide range of applications in engineering, science, and industry. It provides solutions to a variety of real-life problems in the fields of health, business, government, military, politics, security, education, and many more. This book compiles original and innovative findings on all aspects of computational optimization. It presents various examples of optimization including cost, energy, profits, outputs, performance, and efficiency. It also discusses different types of optimization problems like nonlinearity, multimodality, discontinuity, and uncertainty. Over thirteen chapters, the book provides researchers, practitioners, academicians, military professionals, government officials, and other industry professionals with an in-depth discussion of the latest advances in the field.
Optimization Techniques and Applications with Examples
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.
Practical Optimization Methods
Author: M. Asghar Bhatti
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
The goal of this book is to present basic optimization theory and modern computational algorithms in a concise manner. The book is suitable for un dergraduate and graduate students in all branches of engineering, operations research, and management information systems. The book should also be use ful for practitioners who are interested in learning optimization and using these techniques on their own. Most available books in the field tend to be either too theoretical or present computational algorithms in a cookbook style. An approach that falls some where in between these two extremes is adopted in this book. Theory is pre sented in an informal style to make sense to most undergraduate and graduate students in engineering and business. Computational algorithms are also de veloped in an informal style by appealing to readers' intuition rather than mathematical rigor. The available, computationally oriented books generally present algorithms alone and expect readers to perform computations by hand or implement these algorithms by themselves. This obviously is unrealistic for a usual introductory optimization course in which a wide variety of optimization algorithms are discussed. There are some books that present programs written in traditional computer languages such as Basic, FORTRAN, or Pascal. These programs help with computations, but are of limited value in developing understanding of the algorithms because very little information about the intermediate steps v ' Preface VI -------------------------------------------------------- is presented.