Experiment design and metamodelling

This merge request includes the implementation of the queuing simulation model designed to analyze the impact of various structural parameters on system performance, specifically focusing on queue lengths at different stages. The key components of this simulation include:

Queuing Simulation: Models the arrival, preparation, and recovery stages of the system. Serial Correlation Analysis: Analyzes temporal dependencies in queue lengths across multiple simulation runs. Fractional Factorial Design: Tests 8 configurations of system parameters using a 2^(6−3) experimental design. Regression Analysis: Identifies key parameters influencing average queue length and quantifies their impact. This update also includes flexibility in parameter configuration, allowing users to adjust interarrival times, preparation/recovery times, and the number of units in the system. The simulation provides insights into how these factors interact, with the goal of optimizing system utilization and minimizing waiting times.

The simulation outputs include:

Mean queue lengths for each configuration. Time series data for queue lengths. Autocorrelation values to understand temporal dependencies. Regression analysis results to identify the most significant factors affecting queue lengths.