- Know how to model a combinatorial optimization problem through a linear programming model. - Know the main solution methods and algorithms for combinatorial optimization problems, both exact and heuristic. - Know how to define and effectively approach production planning and scheduling problems. - Know the basics of discrete event simulation, with the goal of simulating a production systems. - Learn to use a simulative model of an automated production system and to implement a scheduler able to optimize the production efficiency.

- Introduction: Automation, planning, scheduling. - Combinatorial Optimization and Linear Programming models with examples in production planning and logistics. - Xpress software (https://www.fico.com/en/products/fico-xpress-optimization) for solving LP models. - Scheduling theory basics. - Simulation of logistic and production systems. - Omnet++ (http://www.omnetpp.org/) : implementing and using simulation models. - Combinatorial Optimization : exact algorithms. - Combinatorial Optimization: heuristic algorithms (Greedy, Local Search, Metaheuristics, Tabu Search, Simulated Annealing, Genetic Algorithms, Matheuristics). - Specific production scheduling problem examples. - Laboratory: integration of an optimization-control scheduling software in a simulated system. - Real world application examples.

The course is based on classes, where theory and examples will be presented, and laboratory activities. In the laboratory two software will be used: Omnet++ for simulating production system models, and FICO-Xpress as a tool for solving hard scheduling problems. The students will solve optimization problems and develop a scheduler and integrate it to the simulation model, with the goal of improving the production system efficiency. Note that It is possible to install Omnet++ and a student version of XPress on personal PCs, in order to work on the laboratory exercises at home as well.

The course is mainly based on the provided slides e course material. Specific books for Models and Algorithms for Combinatorial Optimization and Scheduling: M. Pinedo, "Scheduling: Theory, Algorithms, and Systems", Springer. R. Tadei, F. Della Croce, "Elementi di Ricerca Operativa", Editrice Esculapio. R. Tadei, F. Della Croce, A. Grosso, "Fondamenti di Ottimizzazione", Editrice Esculapio. M. Ghirardi, A. Grosso, G. Perboli, "Esercizi di Ricerca Operativa", Editrice Esculapio. Specific books for Discrete Event Simulation: Cassandras, Lafortune, "Introduction to Discrete Event Systems", Springer. G. Calafiore, "Elementi di Automatica", CLUT. Carlucci, Menga, "Teoria dei sistemi ad eventi discreti", UTET 1998.

Lecture slides; Lecture notes; Exercises; Exercise with solutions ; Lab exercises; Lab exercises with solutions; Video lectures (previous years);

You can take this exam before attending the course

Exam: Written test; Individual project; Group project;

The exam is written, and based on a set of questions and exercises, with the objective of verifying the above mentioned competences (Expected Learning Outcomes). The exam duration is 1,5 hours and it is open-book. The exam gives a maximum of 22 points (minimum 12 for passing). The laboratory activities give a maximum of 10 points. The final evaluation is the sum of the points obtained with the exam and the laboratory project (with 31 being still 30, and 32 being 30L).

In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.