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.