队列模拟服务器

version : 1.0.0

validate_config

Validate M/M/1 configuration parameters Checks parameter validity and system stability condition. Args: arrival_rate: Customer arrival rate (λ) service_rate: Service rate (μ) simulation_time: Simulation duration Returns: Dictionary with validation result: - valid: bool - errors: List[str] (if any) - warnings: List[str] (if any) - utilization: float (if valid)

*arrival_rate(number)

*service_rate(number)

simulation_time(number)

结果（Result）

calculate_metrics

Calculate theoretical M/M/1 performance metrics Uses exact formulas to compute steady-state performance. Args: arrival_rate: λ (customers per time unit) service_rate: μ (customers per time unit) Returns: Dictionary of theoretical metrics: - utilization: ρ = λ/μ - avg_queue_length: L_q = ρ²/(1-ρ) - avg_num_in_system: L = ρ/(1-ρ) - avg_waiting_time: W_q - avg_system_time: W Raises: ValueError: If system is unstable (λ >= μ)

*arrival_rate(number)

*service_rate(number)

结果（Result）

run_simulation

Run M/M/1 queue simulation using SimPy Executes discrete event simulation and returns performance metrics. Args: arrival_rate: λ (customers per time unit) service_rate: μ (customers per time unit) simulation_time: Duration of simulation random_seed: Random seed for reproducibility Returns: Dictionary with: - simulation_metrics: Dict of simulated values - theoretical_metrics: Dict of exact values - comparison: Comparison analysis - config: Simulation configuration used

*arrival_rate(number)

*service_rate(number)

simulation_time(number)

random_seed(integer)

结果（Result）

compare_results

Compare simulation results with theoretical values Analyzes accuracy of simulation by comparing against exact formulas. Args: simulation_metrics: Dictionary of simulated performance metrics arrival_rate: λ used in simulation service_rate: μ used in simulation Returns: Comparison analysis with: - comparisons: Per-metric comparison - mean_abs_error_pct: Average error - max_error_pct: Maximum error - within_10pct: bool - accuracy_grade: Quality assessment

*simulation_metrics(object)

*arrival_rate(number)

*service_rate(number)

结果（Result）

recommend_parameters

Recommend simulation parameters for target utilization Suggests appropriate arrival rate, service rate, and simulation time for a given target utilization level. Args: target_utilization: Desired ρ (default: 0.7) service_rate: Fixed μ (if None, suggests μ=10) min_customers: Minimum customers to simulate Returns: Recommended parameters and expected metrics

target_utilization(number)

service_rate(null)

min_customers(integer)

结果（Result）