# Data Reduction of Digital Twin Simulation Experiments Using Different Optimisation Methods
## 4 Methodology
Step 1 and 2--The simulation run performed on a discrete event simulation model can be time consuming, depending on the difficulty of the discrete event simulation model. The developed simulation optimiser based on client-server architecture allows simulation optimisation experiments to be performed on many remote simulation optimisers--servers. Simulation optimisers are installed on different remote servers. Simulation optimisers perform optimisation experiments with the discrete event simulation model. The simulation optimiser communicates with the client via the assigned port number. The simulation optimiser only waits for the instruction to start the execution of optimisation experiments via the application for remote control of the optimisation experiments. If the version of the running simulation optimiser is older than the current version, the optimiser automatically upgrades to the latest version. * Step 3, 4, and 5--The application for remote control of optimisation experiments is started on the client's computer. The application downloads a list of IP addresses of available server computers. The application detects the state of the simulation optimisers. Each IP address lists these attributes of the series: name of the computer performing the optimisation process; status of the simulation optimiser (whether the optimisation experiment is running, ready to run the series, sending files with results, etc. ); remaining time to the completion of the current series (the time updates after the completion of each optimisation experiment); remaining time to the completion of all series; index of the currently running series/total number of all series to perform; version of the simulation optimiser application. The user can launch multiple simulation optimisers on the server (depending on the computational capacity of the computer). The server can perform multiple independent series with different simulation models because each running optimiser communicates with the client using its assigned port (depending on the number of the licenses of the simulation software). The next figure shows the GUI of the proposed application for remote control of the optimisation experiments running on the simulation optimisers--see Figure 8.  
Step 6--Some methods are very susceptible to the setting of their parameters and this setting greatly affects the behaviour of the method when searching for the global  
Figure 8: Client application GUI—remote control of simulation optimiser running on servers. optimum of the objective function. The user can test different parameter settings of the optimisation methods--series. * Step 7--Simulation optimisers are connected to a remote SQL Server database. This database contains all tested possible solution candidates inside the search space by the remote simulation optimisers (performed simulation experiments with the discrete event simulation model). All simulation optimisers update this SQL server database with performed simulation experiments. The simulation optimiser does not have to perform the simulation run in simulation software, but it only searches for the solution candidate in the databases tested by any other simulation optimiser. The user can also launch another module for collecting the statistics on the use of candidate solutions at the SQL server. We use this module to analyse the relative frequency of using the candidate solutions by the optimisation methods and compare their efficiency of generating new candidate solutions in the optimisation process. * Step 8--The application for remote control of optimisation experiments sends all necessary files with the settings of the optimisation methods, their parameters, and the simulation model with its concrete settings from the client's computer to selected simulation optimisers running on servers. The execution of parallel simulation experiments allows the user to distribute simulation models to different computers (using the simulation optimisers) and enhance computing power in the optimisation process with the DT.