Practical Optimization: A Gentle Introduction

An introduction to the most important topics in applied optimization.

**Tag(s):**
Algorithms and Data Structures

**Publication date**: 01 Nov 2007

**ISBN-10**:
n/a

**ISBN-13**:
n/a

**Paperback**:
n/a

**Views**: 20,278

**Type**: N/A

**Publisher**:
n/a

**License**:
n/a

**Post time**: 20 Apr 2009 07:58:47

Practical Optimization: A Gentle Introduction

An introduction to the most important topics in applied optimization.

Excerpts from the Introduction:

John W. Chinneck wrote:This book is designed as a one-term introduction to the most important topics in applied optimization. It is impossible to cover all of optimization in a one-term course: there are entire yearlong courses on each of the individual topics that we will cover! This book provides a fairly broad survey at a medium depth. There are numerous topics that you should be aware of, but which cannot be covered in an introductory book like this one: brief sketches of these topics appear throughout the book.

The main goals of a course using this book should be to equip students to:

1. recognize problems that can be tackled using the tools of applied optimization,

2. formulate optimization problems correctly and appropriately,

3. solve optimization problems, primarily by selecting and applying the correct solvers, but also possibly by writing special software or hiring experts.

These abilities will be an excellent addition to your skills toolkit, and especially useful as the world becomes more complex and computer-centric. Note that a course in optimization or operations research is required in most MBA courses, in business, industrial engineering (and many other engineering programs), and economics. Such courses are usually a recommended option in computer science as well. These courses are included in all those programs precisely because the material finds so many practical applications.

Tweet

About The Author(s)

No information is available for this author.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Rexx
Microsoft .NET
Perl
PHP
R
Python
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors