Logistics
A.Y. 2026/2027
Learning objectives
The course describes the supply chain operations and functions and the problems related to planning and management of logistic systems, with particular emphasis on optimization problems and on computational techniques to solve them.
Expected learning outcomes
Ability in framing and solving optimization problems in logistics.
Lesson period: Second four month period
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second four month period
Course syllabus
1- The supply chain. Terminology and definitions. Description of the logistics chain and its main components. How a dashboard is made for the analysis of a logistics system, the main KPIs.
2- Forecasting. The problem of demand forecasting. Different models and algorithms for demand forecasting. The least squares method and simple linear regression.
3- Localization of logistic structures. Models and algorithms for localization in space and on graphs.
4- Inventory management. Models of stock systems. Systems with continuous and discrete replenishment. Single product and multi-product systems. Single deposit and multi-deposit systems. Economic order quantity.
5- Theory of queues. Definitions and properties of queue systems. Modelling and analysis of queue systems. The use of a dedicated excel tool..
6- Distribution logistics. Routing problems. Vehicle routing with additional constraints and heuristic algorithms for the solution. Optimal Packing problems. Mathematical models and algorithms.
7- Production logistics. Batch sizing problems. Mathematical models and solving algorithms. If there is time: notes on scheduling problems. Mathematical models and solution algorithms.
2- Forecasting. The problem of demand forecasting. Different models and algorithms for demand forecasting. The least squares method and simple linear regression.
3- Localization of logistic structures. Models and algorithms for localization in space and on graphs.
4- Inventory management. Models of stock systems. Systems with continuous and discrete replenishment. Single product and multi-product systems. Single deposit and multi-deposit systems. Economic order quantity.
5- Theory of queues. Definitions and properties of queue systems. Modelling and analysis of queue systems. The use of a dedicated excel tool..
6- Distribution logistics. Routing problems. Vehicle routing with additional constraints and heuristic algorithms for the solution. Optimal Packing problems. Mathematical models and algorithms.
7- Production logistics. Batch sizing problems. Mathematical models and solving algorithms. If there is time: notes on scheduling problems. Mathematical models and solution algorithms.
Prerequisites for admission
It is advisable to have notions of Linear Programming (LP) and Integer Linear Programming (ILP) (usually taught in the teaching of Operations Research, or Mathematical Programming). This knowledge makes it possible to use mathematical modelling to describe some of the optimization problems encountered in logistics. For those who intend to follow Logistica and do not have notions of LP and ILP will be provided some additional hours (about 6) with the basic notions, at the beginning of lessons.
Teaching methods
Lectures and exercises on personal laptop with dedicated sw.
The dedicated course page on the MyAriel website contains the slides used in class, the exercises presented with their solutions, the exams with their solutions of previous years.
The dedicated course page on the MyAriel website contains the slides used in class, the exercises presented with their solutions, the exams with their solutions of previous years.
Teaching Resources
Introduction to Logistics Systems Management: With Microsoft Excel and Python Examples, 3rd Edition
Gianpaolo Ghiani, Gilbert Laporte, Roberto Musmanno
ISBN: 978-1-119-78939-0 October 2022
Recommended texts for part of the teaching:
chapter 17. "Queuing theory" from the book
Introduction to operations research
Frederick S. Hillier, Gerald J. Lieberman.
New York, New York : McGraw-Hill Education (2021)
ISBN : 9781260579376
Michael L. Pinedo
Scheduling
Theory, Algorithms, and Systems
6th edition: Springer Nature Switzerland AG 2022
ISBN:978-3-031-05920-9
ISBN:978-3-031-05921-6 (eBook)
Gianpaolo Ghiani, Gilbert Laporte, Roberto Musmanno
ISBN: 978-1-119-78939-0 October 2022
Recommended texts for part of the teaching:
chapter 17. "Queuing theory" from the book
Introduction to operations research
Frederick S. Hillier, Gerald J. Lieberman.
New York, New York : McGraw-Hill Education (2021)
ISBN : 9781260579376
Michael L. Pinedo
Scheduling
Theory, Algorithms, and Systems
6th edition: Springer Nature Switzerland AG 2022
ISBN:978-3-031-05920-9
ISBN:978-3-031-05921-6 (eBook)
Assessment methods and Criteria
The exam consists of a written test, which includes open-ended questions and exercises (to be held in the laboratory with the aid of the same dedicated sw used during the course), and an interview.
The test is aimed at evaluating the understanding and learning of the systems, models and algorithms studied in class.
The voting are expressed in thirtieths.
The test is aimed at evaluating the understanding and learning of the systems, models and algorithms studied in class.
The voting are expressed in thirtieths.
INFO-01/A - Informatics - University credits: 6
Lessons: 48 hours
Professor:
Trubian Marco
Shifts:
Turno
Professor:
Trubian MarcoProfessor(s)