CODE 118559 ACADEMIC YEAR 2026/2027 CREDITS 3 cfu anno 2 MANAGEMENT FOR ENERGY AND ENVIRONMENTAL TRANSITION (MEET) 11939 (LM-77 R) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR MAT/09 LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 1° Semester MODULES Questo insegnamento è un modulo di: ORGANIZATION, MARKETING AND DECISION METHODS IN ENERGY BUSINESS AND ENVIRONMENTAL TRANSITION AIMS AND CONTENT LEARNING OUTCOMES The course aims to introduce decision support methods to address complex problems in the energy sector, including environmental challenges and the transition to sustainable solutions. Students will acquire knowledge of various management and optimization techniques, such as mathematical programming, scenario analysis along with key performance indicators and other tools for managing uncertainty AIMS AND LEARNING OUTCOMES The course aims at providing decision support methods to face problems in the energy and environmental sectors. Students will learn how quantitative methods can support decision-making processes in complex systems characterized by multiple objectives and uncertainty. The course introduces optimization and mathematical programming models, scenario analysis techniques, decision theory tools, and methods for evaluating alternative strategies through performance indicators. Applications will focus on energy and environmental challenges related to sustainability and transition processes. The consolidation of the proposed methodologies is supported by the development and discussion of case studies. Methods and models will be implemented and analysed using dedicated software tools. The case studies analysed will foster awareness of personal learning progress and the ability to apply the studied techniques in realistic contexts. Moreover, the solution of real-world problems contributes to the development of critical thinking, creativity, problem-solving abilities and decision-making skills. At the end of the course, students will be able to: analyse a decision problem in the energy and environmental domain; formulate mathematical models to support decision-making; identify and evaluate alternative solutions through scenario analysis; use performance indicators to assess and compare different strategies; analyse decision problems under uncertainty; critically interpret and discuss the obtained results in terms of effectiveness, sustainability and robustness. TEACHING METHODS Please note that this course is delivered online (9 hours online videos + 6 hours in person) via the Learn platform. To request access, students must contact the Settore metodi e contenuti at edunext@aulaweb.unige.it. Traditional lectures are integrated with practical exercises, case-study discussions, seminars and individual/group activities. During the course, active, interactive and constructive teaching methods may be adopted to promote the development of both disciplinary and transversal competencies. Exam accommodations for students with disabilities or SLD Students with a valid disability certificate or a diagnosis of Specific Learning Disabilities (SLD) (under Italian Law 104/1992) or Special Educational Needs (SEN), who are registered with the University’s Inclusion Services, can request compensatory tools and/or dispensatory measures for exams. 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,at inclusione.economia@unige.it, and the Inclusion Office inclusione.studenti@info.unige.it. SYLLABUS/CONTENT Part 1: Introduction to Decision Support and Optimization Decision-making processes in energy and environmental systems Introduction to Operations Research and quantitative decision support From real problems to mathematical models Overview of optimization methods and tools Part 2: Mathematical Programming for Energy Applications Formulation of optimization models Objective functions, constraints and decision variables Examples of optimization problems in energy and environmental systems Introduction to software tools for model implementation Part 3: Scenario Analysis and Decision Making under Uncertainty Decision theory fundamentals Decision trees Scenario generation and evaluation Sensitivity analysis Approaches for managing uncertainty Part 4: Performance Evaluation and Sustainability Assessment Key Performance Indicators (KPIs) Multi-criteria evaluation concepts Trade-off analysis among economic, environmental and operational objectives Comparison and interpretation of alternative solutions RECOMMENDED READING/BIBLIOGRAPHY Teaching materials and references will be provided during the course and made available through AulaWeb. TEACHERS AND EXAM BOARD ELENA TANFANI Ricevimento: Office hours by appointment, in person or via Teams, to be arranged by email with the professor (elena.tanfani@unige.it) LESSONS LESSONS START Please note that online lectures are scheduled to begin on September 28, 2026 (first semester). The 6-hour lectures in-person will take place from November 16 to December 11, 2026 (first semester). Further details about the lecture timetable will be announced at a later date. Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The assessment may include a written examination (quiz with multiple and numerical questions) and the development of a project work (also in groups), according to the modalities communicated at the beginning of the course. ASSESSMENT METHODS Assessment aims to evaluate: knowledge and understanding of the theoretical concepts presented during the course; ability to formulate and analyse decision problems; ability to apply optimization and scenario analysis techniques; ability to interpret results critically and communicate them effectively.
