- 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.

Suggested prerequisites are a basic knowledge of discrete event systems, linear programming models, and a good programming skill.

- 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, meta-heuristics (Tabu Search, Simulated Annealing, Genetic Algorithms, etc), mat-heuristics. - 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, organized in groups, will develop a scheduler and integrate it to the simulation model, with the goal of improving the production system efficiency.

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.

Exam: Computer-based written test using the PoliTo platform; Individual project; Group project;

The exam is remotely done using the Exam platform, integrated with a proctoring software (Respondus), using Lockdown browser, and based on a set of multiple choice and open questions, with the objective of verifying the above mentioned competences (Expected Learning Outcomes). The exam duration is 1 hour. This exam gives a maximum of 20 points (minimum 10 for passing). The laboratory activity will be performed online, with personal and group goals which will be developed by the students on their personal PCs during the course, giving a maximum of 12 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).

Exam: Written test; Computer-based written test using the PoliTo platform; Individual project; Group project;

The exam objective is to verify the above mentioned competences (Expected Learning Outcomes). The onsite exam is written and it is composed by 2-3 numerical and modelling exercises. The duration of the exam is 1h30m and it is open book. The online exam is remotely done using the Exam platform, integrated with a proctoring software (Respondus), using Lockdown browser, and based on a set of multiple choice and open questions. The exam duration is 1h30m. In both cases, the exam gives a maximum of 20 points (minimum 10 for passing). A mandatory project based on the laboratory experiences gives a maximum of 12 points. The project is about developing a scheduler for a given productive system simulated model, with the goal of improving the production system efficiency. The project will be developed during the course, with personal and group goals which will be developed by the students in a Politecnico laboratory (if onsite) on their personal PCs (if online). 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).