Optimization: theory and applcations/ S S Rao

Includes index

Introduction to optimization -- Classical Optimization Techniques -- Linear Programming I: Simplex Method -- Linear Programming II: Additional Topics -- Nonlinear Programming I: One- Dimensional Minimization Methods -- Nonlinear Programming II: Unconstrained Optimization Techniques -- Nonlinear Programming III: constrained Optimization Techniques -- Geometric Programming -- Dynamic Programming -- Integer Programming -- Stochastic Programming -- Further Topics in Optimization

The book consists of twelve chapters and three appendices.
chapter 1 provides an introduction to the optimization techniques. The concepts of design space, constraint surface and contours of objective functions are introduced here.
Chapter 2 reviews the essentials of differential calculus useful in finding the maxima and minima of functions of several variables.
chapter 3 and 4 deal with the solution of linear programming problems.
chapter 5 through 7 essentially deal with the solution of nonlinear programming problems. In chapter 5, the numerical methods of finding the optimum of a function of a single variable are given.
Chapter 6 deals with the methods of unconstrained optimization.
chapter 7 is concerned with the solution of nonlinear optimization problems in the presence of inequality and equality constrains.
Chapter 8 presents the technique of geometric programming.
In chapter 9, the computational procedures for solving discrete and continuous dynamic programming problems are presented.
Chapter 10 introduces integer programming and gives several algorithms for solving integer linear and nonlinear optimization.
Chapter 11 reviews the basic probability theory and presents the techniques of stochastic linear, nonlinear and dynamic programming.
Chapter 12 presents briefly the theory and applications of the critical path method (CPM), program evaluation and review technique (PERT), game theory, quadratic programming and calculus of variations.