• Descripción

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.

• Objetivos y competencias

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.

• Contenidos

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

• Consulta de los materiales que dispone la asignatura

• Información sobre la evaluación en la UOC

La Normativa académica de la UOC dispone que el proceso de evaluación se fundamenta en el trabajo personal del estudiante y presupone la autenticidad de la autoría y la originalidad de los ejercicios realizados.

La falta de originalidad en la autoría o el mal uso de las condiciones en las que se hace la evaluación de la asignatura es una infracción que puede tener consecuencias académicas graves.

El estudiante será calificado con un suspenso (D/0) si se detecta falta de originalidad en la autoría de alguna actividad evaluable (práctica, prueba de evaluación continua (PEC) o final (PEF), o la que se defina en el plan docente), ya sea porque ha utilizado material o dispositivos no autorizados, ya sea porque ha copiado de forma textual de internet, o ha copiado de apuntes, de materiales, manuales o artículos (sin la citación correspondiente) o de otro estudiante, o por cualquier otra conducta irregular.

La calificación de suspenso (D/0) en la evaluación continua (EC) puede conllevar la obligación de hacer el examen presencial para superar la asignatura (si hay examen y si superarlo es suficiente para superar la asignatura según indique este plan docente).

Cuando esta mala conducta se produzca durante la realización de las pruebas de evaluación finales presenciales, el estudiante puede ser expulsado del aula, y el examinador hará constar todos los elementos y la información relativos al caso.

Además, esta conducta puede dar lugar a la incoación de un procedimiento disciplinario y la aplicación, si procede, de la sanción que corresponda.

La UOC habilitará los mecanismos que considere oportunos para velar por la calidad de sus titulaciones y garantizar la excelencia y la calidad de su modelo educativo.

• Consulta del modelo de evaluación

• Evaluación final

This is an online graduate course with a demanding educational program based on quantitative contents.  Therefore, in order to achieve the proposed academic goals and objectives, students must actively participate in the online forums and complete the different activities that constitute the continuous evaluation process.  This continuous evaluation process will consist of a set of deliverables (typically three or four) that must be submitted to the instructor on or before their associated deadlines.  The deliverables might include theoretical concepts as well as practical model developments and analysis.  Also, there will be a final proctored test which will contribute to validate the authorship of the aforementioned deliverables as well as to determine the final score.  More details about this evaluation process will be provided in the course syllabus at the beginning of the academic semester.