Teaching code

4S012439

Academic staff

Giacomo Albi, Franco Zivcovich

Coordinator

Giacomo Albi

Credits

9

Language

Italian

Scientific Disciplinary Sector (SSD)

MAT/09 - OPERATIONS RESEARCH

Period

Secondo semestre LM dal Feb 17, 2025 al May 23, 2025.

Courses Single

Authorized

Lessons timetable Moodle Seminars 0

Learning objectives

Aim of this course is to lead students to be able to understand the basic notions and tools of Operations Research in support of the strategic and operational planning of companies, with a particular emphasis to the optimisation of cost and margins regarding the logistics of transport of goods.
At the end of the course, students will have to show the knowledge and the ability to understand the main optimisation methods of Operations Research. They will also have to show the ability to understand, analyse and implement, also by means of specific software, the optimisation models suitable for solving relevant decision-making problems in the field of the logistics of transport of goods.

Prerequisites and basic notions

Basic knowledge of analysis (numbers, sets, functions), algebra and calculus (equations and unknowns, solution of systems of linear equations), analytical geometry (Cartesian coordinates, straight line and plane equations), linear algebra (vectors and matrices) calculus differential and integral.

Program

The course program will focus on optimization techniques for logistics and supply chain management problems. Various practical applications will be addressed in the form of case studies. In particular, we will initially focus on the basics of optimization and mathematical modeling of a logistics problem, providing various examples; we will then address more specific problems such as: the localization of nodes, the management of warehouses, transport, vehicle routing problems and supplier management. The various problems will be analyzed through the guided use of dedicated software both in terms of mathematical optimization aspects and data analysis and forecasts.
In what follows the detail of the course contents:
*Introduction to logistics optimization: Overview of problems in logistics and supply chain management; introduction to optimization techniques; applications of logistics optimization.
*Linear programming and optimization paradigms: basic notions of Linear Programming, notes on solution methods for PL (simplex), Mixed Integer Linear Programming, modeling techniques, mathematical formulation of constraint structures and notable problems. Multi-Criterion and Multiobjective Optimization, Lagrangian relaxation.
*Localization of logistics nodes: Qualitative and quantitative localization methods, continuous and discrete localization problems, multi-product and coverage problems.
*Warehouse management: Performance metrics and decision issues, warehouse design and equipment selection, storage and picking strategies.
*Transportation Management: Transportation modes and classification of transportation problems, least cost flow problems, traffic assignment and network design.
*Vehicle Routing Problems (VRP): Traveling Salesman Problem (TSP) and VRP variants, capacity and time constraints in vehicle routing, real-time vehicle routing problems.
*Integrated optimization problems: Integrated localization and routing problems, inventory-routing problems.
*Supplier management: Supplier search and selection criteria, supplier evaluation and decision making, supplier evaluation and decision making.
*Forecasting and data analysis in logistics: Qualitative and quantitative methods for data analysis, time series analysis and forecasting.
*Software tools for logistics optimization: Introduction and use of software dedicated to logistics optimization (e.g., Python programming language, and the Gurobi solver).
Optional topics:
- Stochastic models in logistics (stochastic optimization techniques, queuing theory and Markov decision processes).
- Heuristic and meta-heuristic methods, genetic algorithms, simulated annealing and applications.

Bibliography

Didactic methods

Lectures with slides, teacher's notes and hand-on sessions in the classroom.

Learning assessment procedures

Written and oral with the possibility of supplementing the examination with a project and exercises during the course.
To pass the exam, students must demonstrate that:
- They have understood the principles underlying optimization techniques applied to logistics problems.
- They are able to present arguments on the topics of the course in a precise and organic way.
- They know how to apply the knowledge acquired to solve application problems presented in the form of exercises, questions and projects.

Evaluation criteria

Discussed and agreed with the aim that they can be both fair and reasonable.

Criteria for the composition of the final grade

Average of written and oral mark, and possible integration of the grade with the carrying out of projects and exercises.

Exam language

Italiano

Sustainable Development Goals - SDGs

This initiative contributes to the achievement of the Sustainable Development Goals of the UN Agenda 2030. More information on sustainability