This book meets the requirements of engineering/science and management students at graduate and postgraduate level.

The main topics discussed are:

Linear programming, including duality and sensitivity analysis.
Non-linear programming, including quadratic and separable programming.
Transport and assignment problems.
Game theory.
Integer programming, including the travelling salesman problem.
Goal programming, including multi-objective programming.
Network analysis (CPM and PERT).
Sequencing problems.
Dynamic programming.


New to this edition:
Two new chapters - “Introduction to Optimization” and “Classical Optimization Techniques”, more solved and unsolved examples, and a new article on processing 2-jobs through k-machines.

Special features:

A very comprehensive and accessible approach to the presentation of the material.
A variety of solved examples to illustrate the theoretical results.
A large number of unsolved exercises for practice at the end of each section.
Solutions to all unsolved examples are given at the end of each exercise.