| Center |
| Faculty of Mathematics |
| Departament |
| Statistics and Operational Research |
| Lecturers in charge |
| Sin datos cargados |
| Met. Docent |
| In the theoretic classes the concepts and methods of the mathematical programming will be introduced, using examples and by proposing exercices to the students. In the practical classes computer packages will be used to formulate and solve optimization problems. |
| Met. Avaluació |
| The course will be evaluated by means of an exam with theoretical questions and practical problems. |
| Bibliografia |
| · Bazaraa, M., Jarvis, J. and Sherali, H., Linear Programming and Network Flows. Wiley 1990. Second edition. · Bazaraa, M. Sherali, H. and Shetty, C.M., Nonlinear Programming: Theory and Algorithms. Wiley 1993. · Garfinkel, R. and Nemhauser, G., Integer Programming. Wiley Interscience 1972. · Nemhauser , G. and Wolsey, L., Integer and Combinatorial Optimization. Wiley 1988. · Salazar, J.J.: Lecciones de Optimización. (2000) Manuales y Textos Universitarios. Universidad de La Laguna. · Williams, H. Model Building in Mathematical Programming. Wiley 1990. · Winston, W.L., Intoduction to Mathematical Programming: Applications and Algorithms. Duxbury Press 1995. · Wolsey, L.A., Integer Programming, Wiley Interscience 1998. |
| Continguts |
| 1 Introduction 1.1 Modelization and Optimization 2 Linear Programming 2.1 The Linear Problem 2.2 The Revised Simplex 2.3 The Simplex for Bounded Variables 2.4 Decomposition 3 Integer Programming 3.1 Structured Problems in Combinatorial Optimzation 3.2 Cutting Plane Methods 3.3 Branch and Bound Methods 4 Non Linear Programming 4.1 Optimality Conditions 4.2 Un-constrained optimization 4.3 Constrained optimization |
| Objetius |
| This course introduces the Mathematical Programming. The main objective is to provide the student the necessary skills to translate optimization problems into models and then to solve them. We consider three basic models: Linear, Integer and Non-Linear Optimization. The course is strongly oriented to applied optimization, paying special attention to the methods and solving algorithms. |
| URL de Fitxa |