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.