ROSS BALDICK is a professor of electrical and computer engineering at the University of Texas at Austin. His current research involves optimization and economic theory applied to electric power system operations and the public policy and technical issues associated with electric transmission under deregulation. He is an associate editor of IEEE Transactions on Power Systems and the chairman of the System Economics Sub-Committee of the IEEE Power Engineering

• List of illustrations; Preface; 1. Introduction; 2. Problems, algorithms and solutions; 3. Transformation of problems; Part I: Linear simultaneous equations; 4. Case studies; 5. Algorithms; Part II: Non-linear simultaneous equations; 6. Case Studies; 7. Algorithms; 8. Solution of the case studies; Part III: Unconstrained optimization; 9. Case studies; 10 Algorithms; 11. Solution of the case studies; Part IV: Equality-constrained optimization; 12. Case studies; 13. Algorithms for linear constraints; 14. Algorithms for non-linear constraints; Part V: Inequality-constrained optimization; 15. Case studies; 16. Algorithms for non-negativity constraints; 17. Algorithms for linear constraints; 18. Solution of the linearly constrained case studies; 19. Algorithms for non-linear constraints; 20. Solution of the non-linearly constrained case studies; References; Index; Appendices.

'Applied Optimization is an excellent text for rigourously introducing graduate and advanced undergraduate engineers to non stochastic optimization. I also think it serves as an excellent reference for engineers in the field who need a clear introduction to this area of mathematics/operations research.' IEEE Control Systems Magazine

ROSS BALDICK is a professor of electrical and computer engineering at the University of Texas at Austin. His current research involves optimization and economic theory applied to electric power system operations and the public policy and technical issues associated with electric transmission under deregulation. He is an associate editor of IEEE Transactions on Power Systems and the chairman of the System Economics Sub-Committee of the IEEE Power Engineering

• List of illustrations; Preface; 1. Introduction; 2. Problems, algorithms and solutions; 3. Transformation of problems; Part I: Linear simultaneous equations; 4. Case studies; 5. Algorithms; Part II: Non-linear simultaneous equations; 6. Case Studies; 7. Algorithms; 8. Solution of the case studies; Part III: Unconstrained optimization; 9. Case studies; 10 Algorithms; 11. Solution of the case studies; Part IV: Equality-constrained optimization; 12. Case studies; 13. Algorithms for linear constraints; 14. Algorithms for non-linear constraints; Part V: Inequality-constrained optimization; 15. Case studies; 16. Algorithms for non-negativity constraints; 17. Algorithms for linear constraints; 18. Solution of the linearly constrained case studies; 19. Algorithms for non-linear constraints; 20. Solution of the non-linearly constrained case studies; References; Index; Appendices.

'Applied Optimization is an excellent text for rigourously introducing graduate and advanced undergraduate engineers to non stochastic optimization. I also think it serves as an excellent reference for engineers in the field who need a clear introduction to this area of mathematics/operations research.' IEEE Control Systems Magazine

ROSS BALDICK is a professor of electrical and computer engineering at the University of Texas at Austin. His current research involves optimization and economic theory applied to electric power system operations and the public policy and technical issues associated with electric transmission under deregulation. He is an associate editor of IEEE Transactions on Power Systems and the chairman of the System Economics Sub-Committee of the IEEE Power Engineering

• List of illustrations; Preface; 1. Introduction; 2. Problems, algorithms and solutions; 3. Transformation of problems; Part I: Linear simultaneous equations; 4. Case studies; 5. Algorithms; Part II: Non-linear simultaneous equations; 6. Case Studies; 7. Algorithms; 8. Solution of the case studies; Part III: Unconstrained optimization; 9. Case studies; 10 Algorithms; 11. Solution of the case studies; Part IV: Equality-constrained optimization; 12. Case studies; 13. Algorithms for linear constraints; 14. Algorithms for non-linear constraints; Part V: Inequality-constrained optimization; 15. Case studies; 16. Algorithms for non-negativity constraints; 17. Algorithms for linear constraints; 18. Solution of the linearly constrained case studies; 19. Algorithms for non-linear constraints; 20. Solution of the non-linearly constrained case studies; References; Index; Appendices.

'Applied Optimization is an excellent text for rigourously introducing graduate and advanced undergraduate engineers to non stochastic optimization. I also think it serves as an excellent reference for engineers in the field who need a clear introduction to this area of mathematics/operations research.' IEEE Control Systems Magazine