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Using Monte Carlo Simulations

Up to 2 hours
Monte Carlo theory Confidence intervals AnyLogic experiment setup

Course Overview

This session introduces Monte Carlo simulations with a review of the theoretical background, emphasis on confidence intervals, and practical guidance on using Monte Carlo experiments in AnyLogic — including current limitations and workarounds.

Objectives

  • Understand the concept and purpose of Monte Carlo simulations
  • Understand confidence intervals and how to communicate variability in results
  • Learn to configure and run Monte Carlo experiments in AnyLogic
  • Understand current limitations of this experiment type in AnyLogic

Prerequisites

AnyLogic

  • Interface familiarity, View Areas, Agents, Datasets, Events, Functions, Databases

JAVA

  • Variables (primitives), Parameters, Casting

Discrete Events

  • Source, Resources, Service, Sink

Agent-Based Modeling

  • Creating agents, reading characteristics from Excel, database query syntax, state charts

Statistical Foundations

  • Uniform distribution, Triangular distribution

Topics Covered

1. Introduction to Monte Carlo

  • Reasons for variability in simulation model results
  • Definition and purpose of Monte Carlo simulations
  • Why Monte Carlo analysis is essential for robust decision-making

2. Confidence Intervals

  • What confidence intervals are and what they mean
  • Calculating confidence intervals: point estimates, confidence levels, margin of error
  • T-scores vs. Z-scores
  • Communicating varied results to stakeholders using confidence intervals

3. Monte Carlo Experiments in AnyLogic

  • Varied in range vs. freeform — when to use each approach
  • Walkthrough of experiment properties
  • Understanding replications and their role in analysis
  • The varying number of replications problem in AnyLogic (with example)
  • Code and methods to export results from the experiment

4. Noorjax Monte Carlo Library

  • How to use the Noorjax Monte Carlo library for streamlined workflows

5. Hands-On Exercises

  • Apply a freeform Monte Carlo experiment in AnyLogic and export results
  • Apply a varied-in-range Monte Carlo experiment and export results

Acquired Knowledge

By the end of this session, participants will be able to:

  • Explain the purpose and mechanics of Monte Carlo simulations
  • Calculate and interpret confidence intervals for simulation outputs
  • Configure and run Monte Carlo experiments in AnyLogic
  • Export results from Monte Carlo experiments effectively
  • Use the Noorjax Monte Carlo library

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