OVERVIEW

Operations Research and Management Science methods, together with transferable skills such as problem solving, teamwork, and complexity management, are essential tools for supporting decision-making in logistics and transportation systems.

The course provides students with knowledge of key Management Science techniques, including mathematical programming, network optimization, and heuristic approaches, with applications to decision-making problems in logistics and transportation, particularly in the maritime sector for both freight and passenger transport.

The methods covered in the course will be applied to case studies derived from real-world industry problems. These cases will be analyzed through individual and group activities using software tools such as Excel and/or LINGO.

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims to develop students’ ability to analyze complex problems in the field of logistics and transportation, formalize them and translate them into optimization models, solve them, and critically assess the resulting solutions. Particular attention is devoted to maritime transport, both for freight and passenger traffic. Students will gain an understanding of how to integrate optimization models with data science techniques for data analysis and decision support. To this end, optimization software and computational tools will be used. These skills will be consolidated through the analysis and solution of case studies, carried out both individually and in groups, thereby fostering the development of problem-solving and teamwork skills.

AIMS AND LEARNING OUTCOMES

The course aims to provide students with knowledge of optimization methods and tools that are increasingly required to address the complex decision-making problems arising in logistics and transportation systems.

Starting from the analysis of decision-making processes in logistics and transportation, the course introduces optimization approaches designed to support decision makers in identifying efficient solutions.

The consolidation of the proposed methodologies is supported through the development of models based on case studies using optimization software and spreadsheet tools. The software applications employed in the course provide students with an introduction to programming concepts, ranging from Excel macros to simple programming languages for the implementation of mathematical models.

The analysis of real-world problems enables students to develop awareness of their own learning progress and their ability to apply the techniques studied, while identifying potential needs for further skills development. Furthermore, solving problems derived from real systems fosters imagination, creativity, critical thinking, and problem-solving abilities.

Upon successful completion of the course, students will be able to:

• analyze key problems in logistics and freight and passenger transportation systems, identifying decision variables, objectives, and operational constraints;
• formulate decision-making problems;
• formulate and implement linear, integer, and binary programming models;
• solve selected optimization problems arising in logistics and freight and passenger transportation;
• critically evaluate the solutions obtained, assessing their correctness and feasibility;
• perform scenario analyses and compare alternative solutions;
• critically assess their own level of learning and ability to apply the techniques studied, identifying any need for further skills development.

PREREQUISITES

• Linear Programming (LP) and Integer Linear Programming (ILP)
• Graphs and Network Optimization

TEACHING METHODS

The course is delivered in a computer laboratory, allowing all students to actively participate in class activities and work alongside the instructor. Theoretical concepts are integrated with the development and analysis of models using dedicated software tools such as Excel and LINGO.

Some problems will be presented by industry experts and subsequently analyzed and solved in class through group work activities. During the course, assignments will be made available to individual students or groups through the AulaWeb platform.

Students who actively participate in group work and receive a positive evaluation from the instructor may obtain the following Open Badges:

• Learning to Learn Skills – Advanced Level
• Project Development Competence – Basic or Advanced Level

Students with disabilities, SLD or SEN

Students with disabilities, with SLD or with SEN are reminded that, to request exam accommodations, they must first upload their certification to the University website at servizionline.unige.it<https://servizionline.unige.it/>, in the “Students” section. The documentation will be checked by the University’s Services for the Inclusion of Students with Disabilities and with SLD.

At the beginning of the course, students are advised to contact the lecturer to agree on exam arrangements which, while respecting the learning objectives of the course, take individual learning needs into account.

To request compensatory tools or dispensatory measures, students with disabilities or SLD must fill in the dedicated Webform available athttps://unige.it/disabilita-dsa, at least 7 working days before the exam.

Students with SEN may instead send their request by e-mail to the lecturer, copying the Department Representative, Prof. Elena Lagomarsino, atinclusione.economia@unige.it<mailto:inclusione.economia@unige.it>, and the Inclusion Office atinclusione.studenti@info.unige.it<mailto:inclusione.studenti@info.unige.it>.

Requests from students will be assessed by the lecturer and may be approved or rejected.

SYLLABUS/CONTENT

In line with the learning objectives outlined above, the course covers the following topics:

Part I – Analysis of Decision-Making Problems

A. Logistics and Transportation Networks

• Facility location problems
• Network design problems
• Transport service and supply planning
• Route and itinerary planning
• Coverage and scheduling problems

B. Intermodal Logistics Nodes

• Train unloading and loading planning
• Truck appointment systems
• Berth allocation and scheduling in maritime terminals
• Yard management: storage policies and area allocation

C. Logistics and Transport Operators

• Trip planning for intermodal logistics operators
• Pricing strategies for passenger transport services and itineraries

Part II – Methods and Tools for Problem Solving

• Graph theory and network optimization
• Integer and binary linear programming
• Heuristic approaches
• Software tools for modeling and optimization (Excel and/or LINGO)

RECOMMENDED READING/BIBLIOGRAPHY

Course materials (lecture slides, articles, handouts, and other resources) will be made available throughout the semester on the course AulaWeb platform.

Recommended Textbooks

• Hillier, F.S., & Lieberman, G.J., Introduction to Operations Research, 2024 Release ISE, McGraw Hill.
• Ghiani, G., Laporte, G., & Musmanno, R., IIntroduction to Logistics Systems Planning and Control.

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

Second semester.

February 2027

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Student assessment is based on a written examination and a project presentation.

The final assessment may be preceded by one or more mid-term tests.

Online registration is mandatory for all examination sessions.

ASSESSMENT METHODS

Students’ knowledge and understanding of the topics covered during the course will be assessed through a written examination, which will focus primarily on the theoretical aspects of the course.

The ability to apply knowledge, communication skills, and other transferable competences (learning to learn and project development skills) will be assessed through group work activities and project presentations.

Assessment will be based on:

1. Work carried out during class activities;
2. The written examination;
3. The project presentation, evaluated on the basis of the completeness and logical organization of the presentation materials (e.g., PowerPoint slides) and the effectiveness and appropriateness of the oral presentation.

Students may choose to present their project either in English or in Italian.

Students may take the examination in any scheduled examination session. There are no restrictions on the number of examination attempts.