Some O.R. or Statistics problems can only be addressed by Simulation, because the basic models generally used, have basic hypothesis that are too far away from "real world" problems. In this situations, it is important to model the real system and carry out simulations, that will allow different solutions to be tested.
In this course, students will develop their abillities to model systems and simulate them. Usually spreadsheets will be used to develop most simulation models. The Visual Basic module of Excel will also be used.
The e-learning MOODLE platform will be used.
Nelson Fernando Chibeles Pereira Martins
Weekly - 4
Total - 84
Students should have general knowledge of Probability Theory, Statistics and Computer programming.
Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2013). Discrete-event system simulation: Pearson new international edition. Pearson Higher Ed.
Classes will take place in computational laboratories, so that students will be able to develop applications of concepts that were taught.
The e-learning moodle platform will be used.
STUDENTS HAVE A MANDATORY ATTENDANCE TO AT LEAST 16 LESSONS BEFORE BEING ACCEPTED TO EVALUATION
2 Midterm Test (T1 and T2) + Group (or individual) Assignment (GA) + Colection of case studies solved in class (CS)
Course will be concluded if CEN >= 9.5, being
CEN = 0,5 (CT1 + CT2) + 0,3 (CTG) + 0,2 (CS)
Final Grade of an approved student: Round (CEN)
The Midterm Tests may be replaced by a Final Exam.
- Introduction, terminology and basic concepts
- Simulation with spreadsheets (Excel and Excel Visual Basic)
- NPA Generation Methods
- Experimental design and statistical analysis of results; number of simulations; Stopping Criteria; Model calibration; Validation
- Queeing models simulation
Programs where the course is taught: