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Modelli per la Gestione della Produzione
Models for Production Management
Ornella Pisacane

Seat Ingegneria
A.A. 2016/2017
Credits 3
Hours 24
Period II
Language ENG

Prerequisites
Fundamentals of Linear Programming and of duality theory.

Learning outcomes
KNOWLEDGE AND UNDERSTANDING:
The course allows students to acquire the necessary skills for designing, evaluating and using the automatic tools of mathematical optimization. In particular, they will study and examine in depth the algebraic languages for mathematically modeling and the main solvers (both commercial and not) of linear programming and integer linear programming, focusing attention on their use for solving problems of logistic production management. Such skills, by integrating the ones acquired during the course of Operations Research, will develop the knowledge in the field of Industrial Engineering (with regard to the production management, the sector of logistic and transport).
CAPACITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
The knowledge acquired during the course will be expressed through a set of professional skills, among which: 1. the capability to properly model the optimization problems; 2. the capability to identify the solver to use; 3. the capability to interpret the obtained results and to perform sensitivity analysis.
TRANSVERSAL SKILLS:
The exercise to solve a problem, developed (eventually) in a group, will lead to the writing of a report by the students. In this way, the students will improve: 1) their degree of autonomous judgment and of presenting (also in a written form) the obtained results; 2) their communication skills (derived from the work done in group); 3. their autonomous capability of both learning and of concluding.

Program
Review of Linear Programming (LP). Examples of LP models: the product mix problem, the transportation problem, the assignment problem. Models of Mathematical Programming (MP) for production planning and for optimal recource allocation. Models of MP for production scheduling and for lot sizing. Models of MP for facility location and for distribution. Models of MP for project management. Optimization software: LINGO and Solver of electronic spreedsheets.

Development of the examination
LEARNING EVALUATION METHODS
The learning evaluation is based on the discussion of an essay and on an oral test. The essay, individually elaborated, concerns a specific argument addressed during the course, with application to a case study inspired by industrial contexts. The oral test consists of a discussion on two or more arguments addressed during the lessons.

LEARNING EVALUATION CRITERIA
In order to positively pass the learning evaluation, the student has to show to have better understood the arguments addressed during the course: on the mathematical models of problems concerning the production management, on reticular techniques for project management, on the use of optimization software.

LEARNING MEASUREMENT CRITERIA
The mark assigned to the discussion of the individual essay and the one given to the oral test vary between zero and thirty. The final mark, expressed in thirtieths, is obtained by rounding up the arithmetic mean of these two marks.

FINAL MARK ALLOCATION CRITERIA
The learning evaluation is positive if the student reaches a sufficient level, equal to a score of eighteen, in both the discussion of the essay and the oral test. The evaluation equal to a score of thirty is reached by showing a detailed comprehension of the arguments addressed during the course. The laude is, instead, given to the students who show a particular clarity during the oral test and during the organization and presentation of the essay.

Recommended reading
F.S. Hillier, G.J. Lieberman, ”Ricerca operativa 9/ed – Fondamenti”, McGraw-Hill (Italia), 2010; C. Vercellis, ”Ottimizzazione- Teoria, Metodi, Applicazioni”, McGraw-Hill, 2008; F. Pezzella, E. Faggioli, ”Ricerca Operativa: problemi di gestione della produzione”, Pitagora Editrice, Bologna.

Courses

• Ingegneria Gestionale (Corso di Laurea Triennale Fuori Sede (DM 270/04))