Simulation is a discipline conceived to represent, to model and to understand the behavior of complex systems and to predict their future behavior. This course provides students with the necessary knowledge and tools to be able of building complex simulation models, the use of standard simulation languages, the analysis of input data, the design of experiments and the analysis of results. Visualization, use cases and issues related to performance are also discussed in the course.
Person in charge
Pau Fonseca Casas (
Joan Garcia Subirana (
Jordi Montero Garcia (
Common technical competencies
CT2 - To use properly theories, procedures and tools in the professional development of the informatics engineering in all its fields (specification, design, implementation, deployment and products evaluation) demonstrating the comprehension of the adopted compromises in the design decisions.
- To demonstrate knowledge and capacity to apply the principles, methodologies and life cycles of software engineering.
- To demonstrate knowledge and capacity to apply the needed tools for storage, processing and access to the information system, even if they are web-based systems.
Technical Competences of each Specialization
Software engineering specialization
CES1 - To develop, maintain and evaluate software services and systems which satisfy all user requirements, which behave reliably and efficiently, with a reasonable development and maintenance and which satisfy the rules for quality applying the theories, principles, methods and practices of Software Engineering.
- To develop, maintain and evaluate complex and/or critical software systems and services.
CES2 - To value the client needs and specify the software requirements to satisfy these needs, reconciling conflictive objectives through searching acceptable compromises, taking into account the limitations related to the cost, time, already developed systems and organizations.
- To design adequate solutions in one or more application domains, using software engineering methods which integrate ethical, social, legal and economical aspects.
G9 [Avaluable] - Capacity of critical, logical and mathematical reasoning. Capacity to solve problems in her study area. Abstraction capacity: capacity to create and use models that reflect real situations. Capacity to design and perform simple experiments and analyse and interpret its results. Analysis, synthesis and evaluation capacity.
- Critical capacity, evaluation capacity.
Sustainability and social commitment
G2 [Avaluable] - To know and understand the complexity of the economic and social phenomena typical of the welfare society. To be capable of analyse and evaluate the social and environmental impact.
- To take into account the social, economical and environmental dimensions, and the privacy right when applying solutions and carry out project which will be coherent with the human development and sustainability.
G3 [Avaluable] - To know the English language in a correct oral and written level, and accordingly to the needs of the graduates in Informatics Engineering. Capacity to work in a multidisciplinary group and in a multi-language environment and to communicate, orally and in a written way, knowledge, procedures, results and ideas related to the technical informatics engineer profession.
- To understand and use effectively handbooks, products specifications and other technical information written in English.
Being able to write a technical article and correctly express concepts in English language.
Being able to assess the impact of the proposed solutions in the context of Sustainable Development Goals (SDG)
Ability to develop a discrete event simulation system study.
What is a simulation study? A practical approach by presenting a real project that will allow students to identify the phases that must be followed for the development of a valid and useful simulation study.
Simulation and Statistical methods
Randomness as the cornerstone of modeling and experimentation. Statistical distributions, generation of numbers and random variables.
Some known distributions and their application in simulation models. Monte Carlo Methods and simulation sampling process.
Introduction to the main paradigms in simulation and applicability of them. Introducing Netlogo, a specific IDE based on agents-based models. ABM system development.
System modeling and related data.
How to build a simulation model using specification languages like UML, SDL ...
Input data analysis. How to fit empirical data to random distributions.
Discrete Event Simulation (DES)
How a discrete event simulator works, what components are necessary for its development. Integration with third-party applications.
Verification and validation of simulation models.
Methodologies to buid verified, validated and credible simulation models.
Experimental design and output analysis.
Basic concepts and methods, the design of experiments in simulation: Scenarios and experiments. Results quality.
Presentation and defense of a simulation study
Multidisciplinary and team work. Presentation and defense of a simulation study for a client. Goals definition and results presentation quality, discussion and future work.
Fonaments bàsics de la simulació
Introducció a l'assignatura, exemples de sistemes i de models. Revisió històrica.
En aquesta activitat l'estudiant aprendrà les diferents fases associades a un estudi de simulació i l'existència de simuladors específics i genèrics.
Motivar a l'alumne i explicar la importància de la disciplina a través d'exemples reals. Objectives:23 Contents:
En aquesta activitat l'estudiant identificarà l'estreta relació entre l'estadística i els seus mètodes i realitzar un estudi de simulació de qualitat.
Laboratory: GPSS language work from two points of view, the first in which we see the system as a user, working one of two paradigms of discrete simulation. Later we will "open" the system to understand its inner workings and learn the main fetarues of a second paradigm.
Paradigmes de Simulació. L'estudiant aprendrà a utilitzar un IDE específic orientat a modelització basada en agents (ABM), un enfoc a la simulació social, i comprendrà la diferència entre simuladors event-schedulling i time-step Objectives:23 Contents:
Descriure les tècniques més usuals per poder Verificar i Validar (VV&A) els models de simulació. Es posa èmfasi en la necessitat d'utilitzar aquestes tècniques per tal de poder emprar el simulador amb garanties de qualitat. Objectives:123 Contents:
L'estudiant realitzarà el disseny d'experiments que millor s'ajusti el seu estudi per, a posteriori, analitzar els resultats. Prèviament, adaptarà el seu motor de simulació específic per tal que suporti l'execució d'experiments. Objectives:123 Contents:
The course is designed taking into account cooperative learning and problem/project-based learning methodologies, complemented with some theoretical sessions intended to develop the set of deliverables with the best guarantees and achievement.
The subject follows a continuous evaluation method, with reviews of the work carried out in class and the deliverables of the programmed activities. It requires a continuous involvement of the student in all activities in order to be able to reach the course.
Final grade: 0,1*T1+ 0,1*T3 + 0,2*T2 + 0,3*T4 + 0,15*T5+0,15*T6 requires to pass all the work in order to achieve the subject.
T1: Practical work assessing the ability of the student to perform empirical data analysis.
T2: Practical work assessing the ability of the student to develop an agent-based model and G3.1 competence
T3: Practical work assessing the capacity of reasoning and analysis of the student in front of a project of simulation and the competences G9, CES2
T4: Practical work assessing if the student has assimilated the concept of DES and the competences CT2, CES1 in the development of the case study simulator.
T5: Practical work to assess the technical competence CT2.1
T6: Practical work that evaluating the G2 cross-competence
The qualification NP "did not attend" will be given when the student participates in a number of assessment items with an aggregated weight less than 20% of the final grade.