This book provides step-by-step descriptions of how to formulate numerical problems and develops techniques for solving them.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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
Inhaltsangabe
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.
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.
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