Normal view MARC view ISBD view

Optimization techniques and applications with examples

By: Yang, Xin-She.
Material type: materialTypeLabelBookPublisher: New Jersey John Wiley & Sons, Inc. 2018Description: xxxi, 350p. With index.ISBN: 9781119490548.Subject(s): Mathematical optimization | Mathematics -​ Applied | Mathematics -​ Probability and​ statisticsDDC classification: 519.6 Summary: 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. https://www.wiley.com/en-us/Optimization+Techniques+and+Applications+with+Examples-p-9781119490623
Tags from this library: No tags from this library for this title. Log in to add tags.
    average rating: 0.0 (0 votes)
Item type Current location Item location Collection Call number Status Date due Barcode
Books Vikram Sarabhai Library
General Stacks
Slot 1680 (2 Floor, East Wing) Non-fiction 519.6 Y2O7 (Browse shelf) Available 199261

TABLE OF CONTENTS

Part I Fundamentals
1 Mathematical Foundations
2 Algorithms, Complexity, and Convexity

Part II Optimization Techniques and Algorithms
3 Optimization
4 Constrained Optimization
5 Optimization Techniques: Approximation Methods

Part III Applied Optimization
6 Linear Programming
7 Integer Programming
8 Regression and Regularization
9 Machine Learning Algorithms
10 Queueing Theory and Simulation

Part IV Advanced Topics
11 Multiobjective Optimization
12 Constraint-Handling Techniques
13 Evolutionary Algorithms
14 Nature-Inspired Algorithms

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.

https://www.wiley.com/en-us/Optimization+Techniques+and+Applications+with+Examples-p-9781119490623

There are no comments for this item.

Log in to your account to post a comment.

Powered by Koha