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Ricerca Operativa 2
OPERATIONS RESEARCH 2
Ferdinando Pezzella

Seat Ingegneria
A.A. 2015/2016
Credits 9
Hours 72
Period I
Language ENG

Prerequisites
Linear Programming

Learning outcomes
The aim of the course is to provide advanced tools based on models and optimization methods for solving decision problems. On completion of the course the student will be able to formulate decision problems of production management using integer programming models and optimization of networks.

Program
- Unconstrained optimimization - Constrained optimization problems: equality constrained - Transportation problem: mathematical model, properties of the A matrix, simplex method - Assignment problems : mathematical model, hungarian method - Network optimization methods: shortest path, minimum spanning trees, PERT - Maximum flow problem : mathematical model, Ford and Fulkerson’s algorithm - Minimal cost network flow problem: properties of the A matrix and simplex on networks - Linear integer programming models - Dual simplex method - Gomory's cutting plane method - Branch and bound algorithms. - Applications of integer linear programming problems in production management - Applications of integer linear programming problems in logistics management - Combinatorial optimization problems and applications - Traveling salesman problems - Vehicle routing problems - Knapsack problems - Software LINGO ( Linear INteractive Global Optimization ) and Microsoft Excel Solver

Development of the examination
LEARNING EVALUATION METHODS
The evaluation of the students’ learning level consists of an oral examination that is characterized by: --the presentation and the dissertation of an individual essay concerning the arguments addressed during the course. In this essay, the student has to prove his/her ability to use optimization software for solving the problems of production management and Logistics. --the discussion of one or two themes, addressed during the course.

LEARNING EVALUATION CRITERIA
In order to pass the learning evaluation, the student has to prove that he/she has understood the arguments, addressed during the course, among which: --The transportation and the assignment problem; --The mathematical models together with the related solution methods of the most significant network optimization problems; --The network techniques for the projects management; --The mathematical models together with the related methods for solving Integer Linear Programming problems; -- Some applications of the Integer Linear Programming in production management; --Solving some production management mathematical models through both the optimization software LINGO and the Excel Solver.

LEARNING MEASUREMENT CRITERIA
During the practice exercises, the student has to show ability to both model and solve some real-world business management problems through optimization software and the implementation of heuristic approaches.

FINAL MARK ALLOCATION CRITERIA
The result of the learning evaluation will be positive if the student reaches a sufficient level (equal to eighteen points) during both the essay dissertation and the oral examination. The evaluation of thirty points is reached by proving a deep knowledge of the arguments, addressed during the course, together with a good ability to solve the optimization problems. The evaluation of thirty points cum laude is for students who have both showed a particular clarity during the oral examination and developed efficient computer programs for solving optimization problems.

Recommended reading
- Educational material provided by the teacher - F. Pezzella, E. Faggioli, Ricerca Operativa: problemi di gestione della produzione, Pitagora, Bologna

Courses

• Ingegneria Informatica e dell'Automazione (Corso di Laurea Magistrale (DM 270/04))