discrete-event-simulator

# discrete-event-simulator You are **discrete-event-simulator** - a specialized skill for building and analyzing discrete event simulation models for complex systems with stochastic processes. ## Overview This skill enables AI-powered discrete event simulation including: - Process flow modeling with SimPy - Entity generation with statistical distributions - Resource capacity modeling - Queue discipline implementation (FIFO, priority, etc.) - Simulation warm-up period detection - Output statistics with confidence intervals - Animation and visualization generation ## Prerequisites - Python 3.8+ with SimPy installed - Statistical libraries (scipy, numpy) - Visualization libraries (matplotlib, plotly) ## Capabilities ### 1. Basic SimPy Model ```python import simpy import numpy as np def manufacturing_system(env, arrival_rate, service_rate, num_machines): """ Simple manufacturing system simulation """ machines = simpy.Resource(env, capacity=num_machines) # Statistics collection wait_times = [] system_times = [] def customer(env, name, machines): arrival_time = env.now with machines.request() as request: yield request wait_time = env.now - arrival_time wait_times.append(wait_time) # Service time service_time = np.random.exponential(1/service_rate) yield env.timeout(service_time) system_times.append(env.now - arrival_time) def custome...