Modeling and Simulation (Midterm)

• Derived from Latin word simulare, which means "to pretend". - Simulation
• Safety way of conducting an experiment with a system. - Simulation
• Powerful techniques for solving a wide variety of problems. - Simulation
• Can be viewed as the manipulation of a system. - Simulation
• Refers to the computerization of a developed model. - Simulation
• Operational research tool- Simulation
• Advantages:

  • Provides deeper understanding of the system
  • gives better insight
  • saves time and money
  • improve the quality of analysis
• Performance of a complex system is difficult to predict
• experimentation of a physical prototype. - Physical Simulation
• Common type of simulation in line with the system approach- Numerical Simulation
• Simulation uses digital computers to simulate. - Digital Simulation
• Efficiency

  • Higher mission availability
  • Increases operational system availability
  • Transportation avoidance
  • Reduces or eliminates expendable costs
  • Less procurement and operational costs
• Effectiveness

  • Improves proficiency
  • Forms fewer complex activities
  • provides neutral services
  • Greater observation, assessment and/or analysis capability
• Risk Reduction

  • Safety of stakeholders
  • Less environmental impact
  • Machinery and equipment handling
• mathematical simulation technique to generate random sample data based on some known distribution for numerical experiments. - Monte Carlo (Risk Analysis) Simulation
• Important Characteristics of Monte Carlo Simulation:

  • Output must generate random samples
  • Input distribution must be known
  • Result must be known while performing an experiment
• Generalized Flowchart of Monte Carlo Simulation:

  Step 1. Sampling of Random variables

  Step 2. Experimenting numerical problems

  Step 3. Performing statistical analysis on output results
• Focuses on the individual active components of a system. - Agent Based Simulation
• Agent Based Simulation can be used:

  • interaction between entities are complex
  • space is vital
  • population is heterogeneous
• Focuses on the process in a system at a medium level of abstraction. - Discrete Event Simulation
• It is widely used in the manufacturing, logistics, and healthcare industries. - Discrete Event Simulation
• Important characteristics of Discrete Event Simulation:

  • predetermined starting and ending points
  • includes a list of discrete events that occurred
  • list of discrete events which are pending
• Q - number of customers in line

  S - server status at time

  A - Arrival

  D - Departure

  E- stopping event
• Highly abstracted method of modeling and simulation. - System Dynamics Simulation
• It ignores the fine details of a system such as the individuals properties of people - System Dynamics Simulation.
• Commonly found in most systems - Queues
• Mathematical study of the congestion and delays of waiting in line. - Queuing theory
• This theory examines every component of waiting in line to be served. - Queuing theory
• helps in designing balanced system that serves customers quickly efficiency. - Queuing theory
• involves customers requesting - Queuing system
• Queuing system can be referred to as a system of flow
• Strengths of a good Queuing system:

  • Increase operation efficiency
  • improve systems productivity
  • reduce walkaway customers
  • can help in understanding trends within the system
  • increase customers lifetime value
• Weaknesses of a Queuing system:

  • Waiting time due to long queues
  • Queue jumping and reneging
  • minimization of waiting crowds
• usually constructed by scientists. - Queuing models
• goal is to minimize the average number of waiting for customers. - Queuing models
• pertains to anything that arrives at a facility. - Customers
• provides a requested service. - Server
• queuing model are concisely identified. - Kendall notation
• A - interarrival time

  B - service time

  c - number of servers

  N - system capacity

  K - size of the calling population
• N and K are usually dropped if it holds and infinite value