Explore queuing theory for scheduling, resource allocation, and traffic flow applications
Queuing theory is the mathematical study of waiting lines or queues. This approach is applied to different types of problems, such as scheduling, resource allocation, and traffic flow. It is often applied in:
- Operations research
- Industrial engineering
- Network design
- Computer architecture
You can explore queuing theory by modeling, measuring, and analyzing the arrival times, wait times, and service times of queuing systems.
For details, see MATLAB®, Statistics and Machine Learning Toolbox™ and SimEvents®.
Examples and How To
- M/M/1 Queuing Theory (Example)
- M/D/1 Queuing System (Example)
- G/G/1 Queuing System and Little's Law (Example)
- Generating Entities as a Markov-Modulated Poisson Process (Example)
- Understanding Discrete-Event Simulation, Part 1: What Is Discrete-Event Simulation? (4:29) - Video
- Understanding Discrete-Event Simulation, Part 2: Why Use Discrete-Event Simulation? (3:54) - Video
- Understanding Discrete-Event Simulation, Part 3: Leveraging Stochastic Processes (3:53) - Video
Software Reference
- SimEvents (Documentation)
- Basic Queues and Servers in SimEvents (Documentation)
- Modeling Queues and Servers in SimEvents (Documentation)
- Routing Techniques in SimEvents (Documentation)
- Statistics and Machine Learning Toolbox (Documentation)
- Resource Allocation Optimization with Mixed Integer Optimization (Documentation)
See also: discrete event simulation, SimEvents, Statistics and Machine Learning Toolbox, genetic algorithm, random number, system design and simulation, research with MATLAB
