Production planning and control
Academic Year 2024/2025 - Teacher: ROBERTO ROSARIO CORSINIExpected Learning Outcomes
To achieve specific skills for the implementation and development of methods for solving short-term production planning problems:
- Modeling of production planning problems;
- Resolution of short-term production planning problems;
- Design and implementation of optimization algorithms.
Course Structure
Traditional teaching
Required Prerequisites
Nothing
Attendance of Lessons
The student has to attend at least 70% of the course lessons, see Point 3.1 of the Regolamento Didattico of CLM in Management Engineering
Detailed Course Content
Introduction to scheduling. Scheduling theory. The single machine problem: problems with no delivery dates, problems with delivery dates. Optimization methods for single-machine scheduling problems. Heuristic methods for the single-machine problem. Extensions of the single-machine problem. The parallel machine problem. The scheduling problem of flow shop systems. Python programming for modeling scheduling problems and implementing optimization techniques.
Textbook Information
Principles of Sequencing and scheduling, K. R. Baker and D. Trietsch, Wiley, New Jersey, 2009, ISBN 978-0-470-39165-5.
Course Planning
| Subjects | Text References | |
|---|---|---|
| 1 | Production Scheduling and solution methods | Principles of Sequencing and scheduling, K. R. Baker and D. Trietsch, Wiley, New Jersey, 2009, ISBN 978-0-470-39165-5. |
Learning Assessment
Learning Assessment Procedures
During the course, project works will be developed under the supervision of the professor. The candidates will be called to verify the project works.
Examples of frequently asked questions and / or exercises
- Modeling of a flow shop production system on Python
- Implementation of the tabu search algorithm