This book meets the requirements of Engineering/Science and Management students at graduate and postgraduate level. Main topics discussed in the book are Linear Programming including duality and sensitivity analysis. Non-linear programming including quadratic and separable programming. Transport and assignment problem. Game theory. Integer programming including Traveling Salesman problem. Goal programming including multi-objective programming. Network analysis (CPM and PERT). Sequencing problem. Dynamic programming. New in this Edition Two new chapters, viz., Introduction to Optimization , Classical Optimization Techniques , some more solved, unsolved examples and a new article on processing 2-jobs through k-machines in Chapter 13, have been added in the present edition. Special features of the book 1. A very comprehensive and accessible approach in the presentation of the material. 2. A variety of solved examples to illustrate the theoretical results. 3. A large number of unsolved exercises for practice at the end of each section. 4. Solutions to all unsolved examples are given at the end of each exercise.