Modeling and Simulation in computer science

Chapters

1Foundations of Modeling in Computer Science

2Mathematical Foundations for Simulation

3Discrete-Event Simulation Fundamentals

Event Scheduling in DES Queueing Theory Basics Process Interaction and Resources State Charts and Event Lists Random Number Generation Interarrival Time Distributions Service Time Distributions Model Building in DES Tools Validation of DES Models Transient vs Steady-State Analysis Throughput and Utilization Metrics Blocking and Deadlocks in DES Cold Start and Warm-Up Periods Parallel DES Execution Case Study: Manufacturing DES

4Agent-Based Modeling and Complex Systems

5System Dynamics and Continuous Modeling

6Numerical Methods and Scientific Computing for Simulation

7Stochastic Processes and Uncertainty Quantification

8Data Structures, Algorithms, and Simulation Efficiency

9Simulation Programming Languages and Frameworks

10Verification, Validation, and Experiment Design

11Performance Analysis and Optimization of Simulations

12High-Performance Computing and Parallel Simulation

13Data Management, Reproducibility, and Experiment Tracking

14Visualization and Communication of Simulation Results

15Applications and Case Studies in Modeling and Simulation

Courses/Modeling and Simulation in computer science/Discrete-Event Simulation Fundamentals

Discrete-Event Simulation Fundamentals

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Explore discrete-event simulation (DES) as a powerful tool for modelling systems where state changes are event-driven.

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Transient vs Steady-State Analysis

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