Part I Fundamentals

1 Introduction

1.1 Opening Perspectives
1.2 Role of Modelling and Simulation
1.3 The Nature of a Model
1.4 An Example Project (Full-Service Gas Station)
1.5 Is There a Downside to the Modelling and Simulation Paradigm?
1.6 Monte Carlo Simulation
1.7 Simulators
1.8 Historical Overview
1.9 Exercises and Projects

2 Modelling and Simulation Fundamentals

2.1 Some Reflections on Models
2.2 Exploring the Foundations
2.2.1 The Observation Interval
2.2.2 Entities and Their Interactions
2.2.3 Data Requirements
2.2.4 Constants and Parameters
2.2.5 Time and Other Variables
2.2.6 An Example: The Bouncing Ball
2.3 The Modelling and Simulation Process
2.3.1 The Problem Description
2.3.2 The Project Goal
2.3.3 The Conceptual Model
2.3.4 The Simulation Model
2.3.5 The Simulation Program
2.3.6 The Operational Phases
2.4 Verification and Validation
2.5 Quality Assurance
2.5.1 Documentation
2.5.2 Program Development Standards
2.5.3 Testing
2.5.4 Experiment Design
2.5.5 Presentation/Interpretation of Results
2.6 The Dynamic Model Landscape
2.6.1 Deterministic and Stochastic
2.6.2 Discrete and Continuous
2.6.3 Linear and Non-linear
2.7 Exercises and Projects

Part II DEDS Modelling and Simulation

3 DEDS Stochastic Behaviour and Modelling

3.1 The Stochastic Nature of DEDS Models
3.2 DEDS-Specific Variables
3.2.1 Random Variates and RVVs
3.2.2 Entities and Their Attributes
3.2.3 Discrete-Time Variables
3.3 Input
3.3.1 Modelling Exogenous Input
3.3.2 Modelling Endogenous Input
3.4 Output
3.5 DEDS Modelling and Simulation Studies
3.6 Data Modelling
3.6.1 Defining Data Models Using Collected Data
3.6.2 Does the Collected Data Belong to a Homogeneous Stochastic Process?
3.6.3 Fitting a Distribution to Data
3.6.4 Empirical Distributions
3.6.5 Data Modelling with No Data
3.7 Simulating Random Behaviour
3.7.1 Random Number Generation
3.7.2 Random Variate Generation

4 A Conceptual Modelling Framework for DEDS

4.1 Introduction
4.1.1 Exploring Structural and Behavioural Requirements
4.1.2 Overview of the Constituents of the ABCmod Framework
4.2 Essential Features of an ABCmod Conceptual Model
4.2.1 Model Structure
4.2.2 Model Behaviour
4.3 Conceptual Modelling in the ABCmod Framework
4.3.1 Project Goal: Parameters, Experimentation and Output
4.3.2 High-Level ABCmod Conceptual Model
4.3.3 Detailed ABCmod Conceptual Model
4.4 Examples of ABCmod Conceptual Modelling: A Preview
4.5 Exercises and Projects

5 DEDS Simulation Model Development

5.1 Constructing a Simulation Model
5.2 The Traditional World Views
5.2.1 The Activity Scanning World View
5.2.2 The Event Scheduling World View
5.2.3 The Three-Phase World View
5.2.4 The Process-Oriented World View
5.3 Transforming an ABCmod Conceptual Model into a Three-Phase Simulation Model
5.4 Transforming an ABCmod Conceptual Model into a Process-Oriented Simulation Model
5.4.1 Process-Oriented Simulation Models
5.4.2 Overview of GPSS
5.4.3 Developing a GPSS Simulation Model from an ABCmod Conceptual Model
5.5 Exercises and Projects

6 The Activity-Object World View for DEDS

6.1 Building Upon the Object-Oriented Programming Paradigm
6.2 Implementing an ABCmod Conceptual Model Within the Activity-Object World View
6.2.1 Overview
6.2.2 Execution and Time Advance Algorithm
6.3 ABSmod/J
6.3.1 The AOSimulationModel Class
6.3.2 Equivalents to ABCmod Structural Components
6.3.3 Equivalents to ABCmod Procedures
6.3.4 Behaviour Objects
6.3.5 Bootstrapping and Evaluating Preconditions
6.3.6 Output
6.3.7 Summary
6.4 Examples of Activity-Object Simulation Models
6.4.1 Kojo’s Kitchen
6.4.2 Port Version 2: Selected Features
6.4.3 Conveyor Project: Working with Entity Categories of Scope = Many[N]
6.5 Closing Comments
6.6 Exercises and Projects

7 Experimentation and Output Analysis

7.1 Overview of the Issue
7.2 Bounded Horizon Studies
7.2.1 Point Estimates
7.2.2 Interval Estimation
7.2.3 Output Analysis for the Kojo’s Kitchen Project
7.3 Steady-State Studies
7.3.1 Determining the Warm-up Period
7.3.2 Collection and Analysis of Results
7.3.3 Experimentation and Data Analysis for the Port Project (V1)
7.4 Comparing Alternatives
7.4.1 Comparing Two Alternatives
7.4.2 Comparing Three or More Alternatives
7.5 Design of Experiments
7.5.1 Introduction
7.5.2 Examples of the Design of Experiment (DoE) Methodology
7.6 Exercises and Projects

Part III CTDS Modelling and Simulation

8 Modelling of Continuous-Time Dynamic Systems

8.1 Introduction
8.2 Some Examples of CTDS Conceptual Models
8.2.1 Simple Electrical Circuit
8.2.2 Automobile Suspension System
8.2.3 Fluid Level Control
8.2.4 Population Dynamics
8.3 Safe Ejection Envelope: A Case Study
8.4 State-Space Representation
8.4.1 The Canonical Form
8.4.2 The Transformation Process

9 Simulation with CTDS Models

9.1 Overview of the Numerical Solution Process
9.1.1 The Initial Value Problem
9.1.2 Existence Theorem for the IVP
9.1.3 What Is the Numerical Solution to an IVP?
9.1.4 Comparison of Two Preliminary Methods
9.2 Some Families of Solution Methods
9.2.1 The Runge–Kutta Family
9.2.2 The Linear Multistep Family
9.3 The Variable Step-Size Process
9.4 Circumstances Requiring Special Care
9.4.1 Stability
9.4.2 Stiffness
9.4.3 Discontinuity
9.4.4 Concluding Remarks
9.5 Options and Choices in CTDS Simulation Software
9.6 The Safe Ejection Envelope Project Revisited
9.7 Exercises and Projects

Part IV Simulation Optimization

10 Optimization Overview

10.1 Introduction
10.2 Methods for Unconstrained Minimization
10.2.1 Gradient-Dependent Methods
10.2.2 Heuristic Methods
10.3 Exercises and Projects

11 Simulation Optimization in the CTDS Domain

11.1 Introduction
11.2 Problem Statement
11.3 Some Representative Forms for the Criterion Function
11.4 Using Gradient Dependent Methods
11.5 An Application in Optimal Control
11.6 Dealing with Computational Overhead
11.7 Exercises and Projects

12 Simulation Optimization in the DEDS Domain

12.1 Introduction
12.2 Problem Statement
12.3 Overview of Search Strategies
12.4 A Case Study (ACME Manufacturing)
12.4.1 Problem Outline
12.4.2 Experimentation

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