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Single discipline educational activity
Course Sheet Academic Year of enrolment:
Professor and Collaborators:
Hours of classroom activity:
Objectives Contents The course introduces a basic segment of optimization problems (Linear Programming, Integer Linear Programming), and tries to show how different problems from real life can be modelled and solved by that discipline.
Extended Syllabus Introduction: Mathematical Programming, Convex Programming, Linear Programming.
Models: models of (Integer) Linear Programming.
Essentials on Linear Programming: geometry of Linear Programming (vertices and basic solutions), Simplex Method; Duality in Linear Programming: Dual Problem, fundemantal properties, economic interpretation.
Essentials on Integer Linear Programming: Unimodularity, Branch and Bound Method.
Solution of (Integer) Linear Programming via Excel Solver.
Particular Cases and Alternative Solutions:
- Minimum Cost Path Problem: Djikstra Algorithm;
- Project Planning Problem: PERT Method;
- Maximum Flow Problem: Ford and Fulkerson Algorithm, Edmonds and Karp Algorithm;
- Production Planning Problem: Wagner and Whitin Method;
- Plant Location Problem: Local Search Algorithms.
Recommended Bibliography [1] R. Baldacci, M. Dell’Amico, Fondamenti di Ricerca Operativa, Pitagora Editrice Bologna (2002) (in eventuale alternativa a [2]).
[2] M. Fischetti, Lezioni di Ricerca Operativa, Ed. Libreria Progetto Padova (1999).
[3] A. Sassano, Modelli e Algoritmi della Ricerca Operativa, Ed. Franco Angeli (1999).
[4] S. Martello, M. G. Speranza, Ricerca Operativa per l'Economia e per l'Impresa, Ed. Esculapio (2012)
Methods of Provision Teaching Methods Evaluation methods Verification of learning:
Written exam, oral test (optional)
