نظرة عامة على البرنامج

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DECISION METHODS FOR SYSTEMS AND NETWORKS MANAGEMENT

Overview

The course aims at exploring tools to support networks and system management, and project management in the energy field, including environmental and green transition issues. Methods to perform network and systems scenarios analysis are presented, together with some Key performance indexes. Models to plan and control the project activities are proposed and time-cost trade-off analysis will be realized.

Aims and Content

Learning Outcomes

The course aims to teach tools that support systems, network management, and project management. It focuses on strategic decisions regarding network design with predefined levels of connectivity, reliability, and sustainability, transitioning from network to system concepts. Decision theory tools will be employed to perform system analysis and dimension evaluation using Key Performance Indicators (KPIs). Several scenario analyses will be performed, and methods for handling uncertainty will be introduced. Within the project management domain, useful models will be examined to plan and oversee project activities. Time-cost trade-off analysis will be conducted.

Aims and Learning Outcomes

The course aims at providing decision support methods to face problems in the energy field, including environmental and green transition issues. The course will provide the knowledge of different management and optimization techniques such as math programming, decision theory, simulation, scenario analysis.

The consolidation of the proposed methodologies is supported by the development of case studies; methods and models will be implemented and solved thanks to specific software.

The case studies analysed will allow the development of awareness of personal learning level, of ability to apply the studied techniques, understanding one's own needs for skills development. Furthermore, the solution of the problems contextualized in real systems allows the development of imagination, creativity, critical reflection, and problem-solving.

With reference to learning outcomes, at the end of the course the students must have acquired competences that allow them to:

• analyse a decision problem and understand the best way to face it
• formulate a decision problem and define a solution approach
• solve some of the typical problems in the energy field
• critically analyse the solutions obtained by assessing their correctness and feasibility and discuss on their efficiency, reliability and sustainability
• carry out scenario analyses and compare the alternatives

Prerequisites

Fundamentals on mathematics and statistics

Teaching Methods

Traditional lectures are integrated with lab lessons, seminars and individual/group works. During lessons, activities based on active, interactive and constructive teaching techniques are proposed; these activities will contribute to the acquisition of transversal skills and related Open Badges.

Thanks to participation in proposed activities, it is possible to obtain the following Open Badge:

• Ability in learning to learn - advanced level
• Project creation proficiency - basic or advanced level

Students who have valid certification of physical or learning disabilities and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Elena Lagomarsino, the Department's disability liaison.

Syllabus/Content

• Part I: Introduction to Optimization models
  • Introduction to Operations Research and problem solving: from real problems to optimization models
  • Classification of optimization models and methods, and brief introduction
  • Software for optimization: excel and/or Lingo
• Part 2: Network Optimization
  • Graphs and Optimization problems on graphs
  • Network design problems, sustainable and reliable networks
• Part 3: Uncertainty and Scenarios Analysis
  • Decision trees and decision theory
  • Simulation and Scenarios analysis
  • System performance evaluation: Key performance indexes, trade-offs
• Part 4: Project Management
  • Graphs for representing and evaluating time and costs of projects
  • Time-cost trade-off analysis
  • Methods to deal with uncertainty

Recommended Reading/Bibliography

Materials and textbook will be indicated during lessons and published on AULAWEB

Teachers and Exam Board

• ELENA TANFANI
• HAOQI XIE

Exam Board

• ELENA TANFANI (President)
• HAOQI XIE (President)

Lessons

Lessons Start

I semester - check the official timetabling at the Department of Economics website (Lessons timetable | DIEC)

Class Schedule

The timetable for this course is available here: Portale EasyAcademy

Exams

Exam Description

Written examination and presentation of case studies. For attendant students, some lab activities (communicated in Aulaweb) will be evaluated for the final grade.

Assessment Methods

The knowledge on the topics covered in class will be assessed through the written examination. The ability to apply knowledge and communication skills and other personal competencies (learning to learn and project creation) will be assessed through the projects work and their presentation.

Exam Schedule

• 17/12/2025 | 11:30 | GENOVA | Scritto
• 22/01/2026 | 11:30 | GENOVA | Scritto
• 05/02/2026 | 11:30 | GENOVA | Scritto
• 29/05/2026 | 11:30 | GENOVA | Scritto
• 12/06/2026 | 11:30 | GENOVA | Scritto
• 15/07/2026 | 11:30 | GENOVA | Scritto
• 03/09/2026 | 11:30 | GENOVA | Scritto

Further Information

Working students and students with certified SLD (Specific Learning Disorders), disability or other special educational needs are advised to contact the teacher at the beginning of the course to agree on teaching and examination arrangements so to take into account individual learning patterns, while respecting the teaching objectives.

Agenda 2030 - Sustainable Development Goals

• Affordable and clean energy
• Sustainable cities and communities
• Climate action

OpenBadge

• SOFT SKILLS - Creazione progettuale avanzato 1 - A
• SOFT SKILLS - Creazione progettuale base 1 - A
• SOFT SKILLS - Imparare a imparare avanzato 1 - A