After successful completion of this module component, the student is able to:
- select appropriate models and methods (from those provided in the Stochastic Models component) that are relevant to the given practical problem that is a simplified version of the real-world problem but still too large to solve by hand;
- analyse the problem by implementing the selected models and methods in computer code to draw conclusions about the behaviour of the system.
- design and implement a conceptual simulation model in a simulation environment, according to the project specifications.
- perform simulation experiments, interpret the outcomes of the simulation, and formulate recommendations that are useful for the problem owner.
- apply construction and improvement heuristics and local search heuristics to solve the simplified version of the real-world problem.
- analyse the requirement of the real-world problem and implement relevant methods and theory to solve the problem.
- select appropriate modelling tools (from the set of tools provided in this module) for the real-world problem, and use them to model and solve the problem;
- Integrate the theory, techniques, and applications of the aforementioned tools to to analyse, model, and solve the problem.
- interpret the outcomes of the aforementioned tools and formulate practical recommendations for system improvement via effective communication and collaboration with group members.inform and convince the problem owner by means of a report and presentation
- inform and convince the problem owner by means of a report and presentation.
|
 |
|
In the module component Project MASP, students work together in a project group. This component has one theme and is related to a real-world problem. The project design considers applying and integrating the theory learned in the stochastic models, and simulation & heuristics. It has three parts and multiple deliverables.
-
-
- Stochastic Models Part – 2 EC
- Simulation and Heuristics Part – 2 EC
- Integration, expansion, and project MASP report – 3 EC
In the first two components (Stochastic Models Part and Simulation and Heuristics Part), students work on simplified versions of the real-world problem.
The first part mainly considers the Stochastic Models component, where students learn to apply stochastic dynamic programming and queueing theory to solve large problems that cannot be solved by hand. Mathematical Modelling and implementation in a computer are the main ingredients.
Second, students build further on the Simulation and Heuristics component and learn how to use computer simulation to gain insight into stochastic systems that are still too complex to analyse via other means. Students need to analyse the system to be simulated, implement a model into discrete-event simulation software, implement heuristics for planning and scheduling and priority rules, and perform a proper statistical analysis in order to draw conclusions about the performance of the system. Third, students need to work on the real-world problem (the assumptions and simplifications of the first two parts are relaxed). They will select appropriate methodologies and apply them to the real-world problem and finally integrate methods and results into a solid report that shows the steps taken to solve the real-world problem. At the end of the module, the project will be briefly presented by each group of students.
|
|
|
This Project MASP takes place during the module and has three parts.
- Stochastic Models Part – 2 EC
- Simulation and Heuristics Part – 2 EC
- Integration, expansion, and project MASP report – 3 EC
To participate in the third part of the project, a serious effort in both theory parts and first two parts of the project is required. The third part of the project receive a grade if part 1 and 2 of the project is passed. The project MASP receive a passing grade if all parts of the project receive a passing grade. If any part of the project is passed and project MASP is not receive a passing grade, the score of passed parts remain valid for the next year. The precise details can be found in the module manual.
|
|