OVERVIEW

The quantitative methods characteristic of operations research and management science, together with soft skills relating to problem-solving and teamwork, are now universally recognised as indispensable tools for decision-making in the analysis and operation of complex systems, such as logistics and transport systems. Those working in the maritime logistics sector cannot therefore do without knowledge of and the ability to use these tools, and in particular the simulation and data analysis techniques required to evaluate the performance indicators of interest in port systems.

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims to provide tools and optimization methods that are increasingly essential for addressing the complex challenges in the management of maritime terminal operations, as well as highlighting the benefits of integrating optimization with data science techniques. The consolidation of the proposed methodologies is facilitated by the development of models based on case studies created using optimization software and spreadsheets.

AIMS AND LEARNING OUTCOMES

The main aim of the course is to provide the skills required to analyse complex systems relating to port logistics. Key performance indicators in the maritime and port sector will be assessed, equipping students with a thorough understanding of the decision-making methods to be used in an uncertain and dynamic context, as well as the tools currently available.
The expected learning outcomes, including the acquisition of soft skills, are:
•    the ability to identify and analyse phenomena that impact the efficiency of port operations, identifying decision-making factors, objectives and operational constraints;
•    the ability to identify and analyse the various processes that make up complex systems, characterised by dynamic and uncertain elements;
•    the ability to use advanced software environments, such as Witness Horizon, for the interactive graphical simulation of complex systems in the field of port logistics;
•    consolidation of proficiency in the use of spreadsheets, such as Excel, for data entry, analysis and scenario analysis;
•    ability to independently propose and analyse case studies relating to problems discussed in class;
•    problem-solving skills;
•    teamwork skills;
•    ability to retrieve data using search engines and websites;
•    public speaking skills.

PREREQUISITES

To successfully complete this course, students are expected to have a basic knowledge of the concepts covered in mathematics and statistics courses. A basic understanding of the problems and solution methods involved in operations research, as well as planning techniques, is also required.

TEACHING METHODS

The course takes place in a computer lab, giving all students the opportunity to actively participate in lessons and work alongside the lecturer, combining theory with the definition, development and analysis of various models and case studies. The course includes group work and presentations by business representatives.

SYLLABUS/CONTENT

In line with the objectives described above, the course content is as follows:
1.    Terminal productivity indicators, calculated on the basis of steady-state or transient behaviour of the system.  Efficiency indices: productivity (quantity or resources allocated); cost. Time indices: service indices; waiting times.
2.    Analysis of maritime terminal operations. Optimal sizing of port service centres (berths, gates, equipment). Analysis of congestion situations. Queuing theory. Performance analysis in queuing systems and queuing networks
3.    Introduction to discrete-event simulation. Definition of DES system and model. Criteria for selecting input data. Conducting a simulation experiment. Validation of a simulation model.
4.    Use of the Witness discrete-event simulation software environment for the analysis of complex systems in port logistics. Input and definition of elements. Dynamics and flow rules of system components. Determination and visualisation of system performance indices. Evaluation of the system’s cost/performance trade-offs. Development and analysis of case studies using discrete-event simulation.
5.    Use of Excel and other software environments for formulating and solving operations planning problems and for data analysis.
•    During the course, there will be guest speakers, and case studies will be presented and evaluated in class.

RECOMMENDED READING/BIBLIOGRAPHY

Course materials (slides, articles, handouts, etc.):
•    Materials provided by the lecturer, slides and videos uploaded to Aulaweb and/or the course’s Teams platform.
Recommended textbooks:

• F. S. Hillier, G. L. Lieberman. “Introduction to Operations Research”. McGraw Hill, 2016 (only suggested sections);
• A.M.Law, Simulation modeling and analysis, IV edizione, McGraw-Hill, 2007 (only suggested sections);
• G. Iazzeolla. Principi e Metodi di Simulazione Discreta. Franco Angeli, 2010 (only suggested sections);
• J. Banks, J.S. Carson,B.L. Nelson, D.M.Nicol, Discrete Event System Simulation, Prentice-Hall,2001 (only suggested sections).

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

The lessons take place in the first semester

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The examination consists of a written paper and an oral examination. Only students who pass the written paper with a mark of over 18/30 are eligible to sit the oral examination.

The oral examination will also be marked out of 30. The final mark will be determined by the average of the marks obtained in the written paper and the oral examination.

Up to a maximum of 3 points may also be added to the final mark, as determined by the lecturer during the oral examination, based on any clarifications regarding the conduct of the written examination and the marking of the written paper.

ASSESSMENT METHODS

Assessment will be based on a written examination, the presentation of a group project delivered in class, work completed in class, and active participation during lessons.
For non-attending students, the oral examination will also assess their ability to present ideas and analyse the issues and methods covered.

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.