Simulación Código:  M0.500    :  6
Consulta de los datos generales   Descripción   La asignatura en el conjunto del plan de estudios   Campos profesionales en el que se proyecta   Conocimientos previos   Información previa a la matrícula   Objetivos y competencias   Contenidos   Consulta de los recursos de aprendizaje de los que dispone la asignatura   Informaciones sobre la evaluación en la UOC   Consulta del modelo de evaluación  
Este es el plan docente de la asignatura para el segundo semestre del curso 2023-2024. Podéis consultar si la asignatura se ofrece este semestre en el espacio del campus Más UOC / La universidad / Planes de estudios). Una vez empiece la docencia, tenéis que consultarlo en el aula. El plan docente puede estar sujeto a cambios.
Welcome to this graduate course on Discrete-Event Simulation, a hybrid discipline that combines knowledge and techniques from Operations Research (OR) and Computer Science (CS). Due to the fast and continuous improvements in computer hardware and software, Simulationhas become an emergent research area with practical industrial and services applications.  Today, most real-world systemsare too complex to be modeled and studied by using analytical methods.  Instead, numerical methods such as simulation must be employed in order to study the performance of those systems, to gain insight into their internal behavior and to consideralternative ("what-if") scenarios.  Applications of Simulations are widely spread among different knowledge areas, including the performance analysis of computer and telecommunication systems or the optimization ofmanufacturing and logistics processes.  This course introduces concepts and methods for designing, performing and analyzing experiments conducted using aSimulation approach.  Among other concepts, this course discusses the proper collection and modeling of input data and system randomness, the generation of random variables to emulate the behavior of the real system, the verification and validation of models, and the analysis of the experimental outputs.

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This is a compulsory subject within the master's program.

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The aim of this course is to train students to develop their professional careers within the following fields:
* Research
* Computer Simulation
* Artificial intelligence
* Operation Research
* Any related field

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This course is designed for postgraduate students in any of the following degrees: Computer Science, Telecommunications Engineering, Business Administration, Industrial Engineering, Economics, Mathematics or Physics. 

Some mathematical knowledge is required. It is assumed that the student has successfully completed at least three undergraduate courses in mathematics, one of them in probability and statistics. In addition, some programming knowledge is desirable but not essential. Finally, the student must be able to read the technical documentation written in English.

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Description: This course allows the student to know the concepts and acquire the necessary skills to model and simulate systems, networks and processes through the use of Monte Carlo Simulation (MCS) and Discrete Event Simulation (DES) techniques. For this, the course includes theoretical-practical learning of data modeling methods associated with random phenomena, generation of pseudo-random numbers, design of simulation algorithms, design of experiments, verification and validation, analysis of results, and comparison of alternative designs. The course also includes the learning of specific software for modeling and simulation (e.g. Ape, etc.), as well as its use in the study and resolution of practical cases in different fields of knowledge.

Requirements: Ability to read scientific texts in English. Basic knowledge of statistics (undergraduate or engineering level).

Planned bibliography: Robinson, S. (2004). Simulation: The Practice of Model Development and Use. Wiley.

Planned software: SIMIO Simulation Software (http://www.simio.com)

Links: WSC Archive (http://informs-sim.org)

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The main goals of this course are:

  • To introduce students in the prolific research field of discrete-event simulation. In particular, this course offers a set of powerful system modeling and analysis tools (concepts, techniques and skills) that students can use both in their research and professional careers.
  • To develop students' modeling, analytical-thinking and synthesis skills.  In particular, throughout the course students will have to: model systems or processes in order to analyze them, read scientific papers, and develop their own simulation skills.

Course objectives are derived from the course goals and designed to be assessable. By the end of this course, students should be able to:

  • Apply scientific thinking to the analysis ofcomplex systems and processes.
  • Comprehend important concepts in computer modeling and simulation.
  • Model uncertainty and randomness by means of statistical distributions.
  • Form a hypothesis and design acomputer experiment to test it.
  • Collect and model data, estimate errors in the results and analyze simulation outputs.
  • Understand how computers generate (pseudo-)random numbers and variables.
  • Realize the application scope and limitations of computer simulation techniques.
  • Employ statistical techniques to construct scientific statements and conclusions.
  • Construct, verify and validate system and processes models.
  • Understand the main ideas described in scientific papers on simulation.

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1. Simulation: What, Why and When? 2. Inside Simulation Software 3. Software for Simulation 4. Simulation Studies 5. Conceptual Modeling 6. Developing the Conceptual Model 7. Data Collection and Analysis 8. Model Coding 9. Obtaining Accurate Results 10. Searching the Solution Space 11. Implementation 12. Verification & Validation 13. The practice of simulation

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Simulation PDF
Simulación con Simio PDF
Simulation with Simio PDF

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El proceso de evaluación se fundamenta en el trabajo personal de cada estudiante y presupone la autenticidad de la autoría y la originalidad de los ejercicios realizados.

La falta de autenticidad en la autoría o de originalidad de las pruebas de evaluación; la copia o el plagio; el intento fraudulento de obtener un resultado académico mejor; la colaboración, el encubrimiento o el favorecimiento de la copia, o la utilización de material o dispositivos no autorizados durante la evaluación, entre otras, son conductas irregulares que pueden tener consecuencias académicas y disciplinarias graves.

Por un lado, si se detecta alguna de estas conductas irregulares, puede comportar el suspenso (D/0) en las actividades evaluables que se definan en el plan docente –incluidas las pruebas finales– o en la calificación final de la asignatura, ya sea porque se han utilizado materiales o dispositivos no autorizados durante las pruebas, como redes sociales o buscadores de información en internet, porque se han copiado fragmentos de texto de una fuente externa (internet, apuntes, libros, artículos, trabajos o pruebas del resto de estudiantes, etc.) sin la correspondiente citación, o porque se ha practicado cualquier otra conducta irregular.

Por el otro, y de acuerdo con las normativas académicas, las conductas irregulares en la evaluación, además de comportar el suspenso de la asignatura, pueden dar lugar a la incoación de un procedimiento disciplinario y a la aplicación, si procede, de la sanción que corresponda.

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Esta asignatura solo puede superarse a partir de la evaluación continua (EC), nota que se combina con una nota de prácticas (Pr) para obtener la nota final de la asignatura.La fórmula de acreditación de la asignatura es la siguiente: EC + Pr.Las calificaciones finales de la asignatura se calcularán de la siguiente manera:
- Si la EC y la Pr superan el mínimo, la calificación final será el resultado de la fórmula de cálculo.
- Si no se supera el mínimo de la EC, la calificación final será la de la EC.
- Si no se presenta la EC, la calificación final será No presentado.
- Si la EC supera el mínimo y la Pr no, la calificación final será la nota de la Pr.
- Si la EC supera el mínimo y la Pr no se presenta, la calificación final será Suspendido (2,5).

 
 

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