Short description This is the only book on the market that discusses all the important methods of optimization. All the methods are presented in a simple language in the most comprehensive manner. Nonlinear, linear, geometric, dynamic and stochastic programming techniques are presented with a focus on engineering applications. Other more specialized methods such as optimal control, multiobjective optimization, genetic algorithms, simulated annealing, neural networks and fuzzy optimization methods are also included. In each case examples and cases are presented to show how the mtheod is actually used in the real world.
From the contents Preface.
1 Introduction to Optimization.
1.1 Introduction.
1.2 Historical Development.
1.3 Engineering Applications of Optimization.
1.4 Statement of an Optimization Problem.
1.5 Classification of Optimization Problems.
1.6 Optimization Techniques.
1.7 Engineering Optimization Literature.
1.8 Solution of Optimization Problems Using MATLAB.
References and Bibliography.
Review Questions.
Problems.
2 Classical Optimization Techniques.
2.1 Introduction.
2.2 Single-Variable Optimization.
2.3 Multivariable Optimization with No Constraints.
2.4 Multivariable Optimization with Equality Constraints.
2.5 Multivariable Optimization with Inequality Constraints.
2.6 Convex Programming Problem.
References and Bibliography.
Review Questions.
Problems.
3 Linear Programming I: Simplex Method.
3.1 Introduction.
3.2 Applications of Linear Programming.
3.3 Standard Form of a Linear Programming Problem.
3.4 Geometry of Linear Programming Problems.
3.5 Definitions and Theorems.
3.6 Solution of a System of Linear Simultaneous Equations.
3.7 Pivotal Reduction of a General System of Equations.
3.8 Motivation of the Simplex Method.
3.9 Simplex Algorithm.
3.10 Two Phases of the Simplex Method.
3.11 MATLAB Solution of LP Problems.
References and Bibliography.
Review Questions.
Problems.
4 Linear Programming II: Additional Topics and Extensions.
