Exploring Multi-Method Simulation

Course Overview

This session introduces multi-method simulation modeling — the art of combining Discrete Event Simulation (DES), System Dynamics (SD), and Agent-Based Modeling (ABM) into a single model. Through healthcare examples, participants will learn when and how to integrate paradigms for more comprehensive system representations.

Objectives

Understand what multi-method simulation is and when it provides value
Gain a foundational understanding of the three main simulation paradigms
Recognize the advantages and challenges of integrating methods into a single model
Explore conceptual best practices and practical applications

Prerequisites

Basic understanding of simulation paradigms (DES, SD, ABM) and their components
Basic understanding of the AnyLogic framework

Topics Covered

1. Overview of Multi-Method Simulation

What is multi-method simulation and when to use it
Brief review of each paradigm:
- DES: Event-driven processes
- SD: Continuous flow and feedback loops
- ABM: Individual entities with autonomous behaviors
Benefits of combining methods for complex systems
Level of abstraction comparison across paradigms
Example: Healthcare simulation integrating DES, SD, and ABM for patient flow, resource allocation, and population trends

2. Challenges and Best Practices

Managing complexity in model interactions
Regular verification and validation at each integration point
Balancing model fidelity with performance

3. Group Activity

Apply knowledge by solving a problem using a given paradigm
Share solutions and discuss how each method addresses different aspects of the problem

Acquired Knowledge

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

Define multi-method simulation and the unique strengths of DES, SD, and ABM
Identify the appropriate simulation paradigm for specific problem types
Understand the challenges in combining paradigms and apply best practices