Home > DECYL (Data, Statistics, Quality and Logistic) > Research lines > Simulation & Optimization Models
The simulation can be considered as a wide range of methods and techniques aimed at imitation and reproduction of the behavior of real systems, usually on a computer. It uses mathematical models of the systems analyzed. The purpose of building a simulation model is to experiment with it rather than experimenting with the real system (too expensive, there is no ethical, etc..). The information obtained from the execution of the simulation model is used to make decisions concerning the real system. Furthermore, the simulation model allows, through the definition of scenarios, answering questions such as what would happen if ...?.
The team has experience in the development of simulation models of complex systems that evolve over time (dynamic ) and have the characteristic of uncertainty (stochastic ) and in the design and use of simulation optimization methods in multicriteria contexts where it is considered simultaneously optimizing some criteria. Proof of this are the real problems in which the team has successfully applied this methodology :
ENGINEERING APLICATIONS:
ENVIROMENTAL APLICATIONS:
HEALTH APLICATIONS: