Logistics
A.Y. 2023/2024
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 semester
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 semester
Course syllabus
1- The supply chain. Terminology and definitions. Description of the logistics chain and its main components.
2- Forecasting. The problem of demand forecasting. Different models and algorithms for demand forecasting. The least squares method and simple linear regression.
3- 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.
4- Logistics of production.
4.1 Lot sizing problems. Mathematical models and solving algorithms.
4.2 Scheduling problems. Mathematical models and solving algorithms.
5- Logistics of distribution
5.1 Optimal Packing problems. Mathematical models and approximation algorithms: first-fit and best-fit.
5.2 Routing problems. Vehicle routing with additional constraints and heuristic algorithms for its solution.
6- Queueing theory
6.1 Definitions and properties of queue systems. Modelling, analysis and synthesis of queue systems.
2- Forecasting. The problem of demand forecasting. Different models and algorithms for demand forecasting. The least squares method and simple linear regression.
3- 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.
4- Logistics of production.
4.1 Lot sizing problems. Mathematical models and solving algorithms.
4.2 Scheduling problems. Mathematical models and solving algorithms.
5- Logistics of distribution
5.1 Optimal Packing problems. Mathematical models and approximation algorithms: first-fit and best-fit.
5.2 Routing problems. Vehicle routing with additional constraints and heuristic algorithms for its solution.
6- Queueing theory
6.1 Definitions and properties of queue systems. Modelling, analysis and synthesis of queue systems.
Prerequisites for admission
Operations Research (recommended)
Teaching methods
Lectures
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 text for part of the course
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 text for part of the course
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, and an interview.
The test is aimed at evaluating the understanding and learning of the systems, models and algorithms studied in the course.
The test is aimed at evaluating the understanding and learning of the systems, models and algorithms studied in the course.
Educational website(s)
Professor(s)