Presentations text content in Introduction to Simulation Methods
Slide1
Introduction to Simulation Methods
Professor Stewart Robinson
Stewart Robinson
Loughborough University
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Slide2Session Outline
What is simulation?
Why use simulation?Four simulation approaches
Stewart Robinson
Loughborough University
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Slide3Stewart Robinson
Loughborough University
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How did British Airways Decide on the Design of Terminal 5?
How many check-in desks?
How many departure gates?
Configuration of security screening
Design of baggage handling system
Size of passport control area?
Flight schedule capacity
Workforce rosters
Slide4Terminal 5 Simulation
Stewart Robinson
Loughborough University
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Source: Beck, A. (2011). Journal of Simulation 5, 69–76
Slide5Stewart Robinson
Loughborough University
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What is Simulation?
Experimentation with a simplified imitation (on a computer) of a ... system as it progresses through time, for the purpose of better understanding and/or improving that system.
(Robinson,
2014
)
Simulation is: an
imitation
of a system
Simulation video
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Loughborough University
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What is Simulation?
A simulation model enables a manager to experiment with alternative courses of action, the simulation providing predictions about the likely outcome. As a result, the manager obtains a better understanding of reality and is able to identify ‘good’ courses of action.
Simulation
model
Inputs
Outputs
Experimentation
Slide7Examples of SimulationFord Motor Company
. Simulation was widely used to aid the planning and design of their Zetec engine plants in South Wales. These represented an investment of $750m.
The simulations helped improve output by around 30%.
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Loughborough University
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Slide8Examples of SimulationEmptying a waste pond and processing the waste to make it safe.
Achievement of waste removal to a specified timeline.
Nuclear Industry
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Loughborough University
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Slide9Examples of SimulationOutpatients Department Rebuild
: investigation of number of consulting rooms required.
Stewart Robinson
Loughborough University
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Slide10Why Use Simulation?Because systems are subject to
variability, are interconnected
and complex.1. Variability:Predictable variability e.g. shift changeovers, preventative maintenanceUnpredictable variability e.g. customer arrivals, breakdown
Stewart Robinson
Loughborough University
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Slide11Why Use Simulation?2. Interconnectedness
Variability does not occur in isolation, but is connected to other sources of variability.
Service 1Service 2Service 3
CustomerarrivalsTime: 10 minsTime: 9 mins
Time: 9 mins
Time: 9 mins
What is the mean time a customer spends in the system?
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Loughborough University
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Slide12Why Use Simulation?3. Complexity
Combinatorial complexity: the number of combinations of system components that are possible.
20 interconnections
2 interconnections
Combinatorial complexity
is related to the size of a system.
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Loughborough University
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Slide13Why Use Simulation?3. Complexity
Dynamic complexity: related to the interaction of components in a system over time.
It is normally associated with feedback e.g. a kanban system:
M1B1Parts
Information
It is not necessarily related to the size of a system.
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Loughborough University
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Slide14Simulation Approaches
Monte Carlo Simulation (not strictly business dynamics)
Stewart Robinson
Loughborough University
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f (a, b, c)
Random sampling process (hence ‘Monte Carlo’)
Not always dynamic (time-based) models
Typical used in finance applications for portfolio management
Slide15Simulation Approaches
Discrete-Event Simulation
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Loughborough University
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World represented as Queues and Activities
Variable time step to represent changes in state of the system
Used for modelling queuing systems e.g. airports, banks, manufacturing plant, call centres, ports, computer systems,...
Slide16Simulation Approaches
Continuous Simulation (e.g. system dynamics)
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Loughborough University
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World represented by Stocks and Flows
Constant (small) time step (
Δ
t
) to approximate continuous time
Typical used in business strategy/policy and more general continuous simulation in science and engineering
Slide17Simulation Approaches
Agent Based Simulation
Stewart Robinson
Loughborough University
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World represented by (intelligent) interacting agents
Constant time step (
Δ
t
) but can be discrete-event
Used for exploring emergent behaviour in organisations as well as other
contexts: e
vacuation
, traffic
flow, stock markets, diffusion
of
innovation, spread of infectious diseases
Boids simulation
Slide18Reading
Discrete-Event Simulation
Robinson, S. (2014). Simulation: The Practice of Model Development and Use, 2nd ed. Palgrave, London. Law, A.M. (2014). Simulation Modeling and Analysis, 5th ed. McGraw-Hill, New York.
System Dynamics Morecroft, J. (2007). Strategic Modelling and Business Dynamics: A Feedback Systems Approach. Wiley, Chichester. Sterman, J.D. (2000).
Business Dynamics: Systems Thinking and
Modeling
for a Complex World
. McGraw-Hill, New York.
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Loughborough University
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Slide19Reading
Agent Based Modelling
Robertson, D.A. and Caldart, A.A. (2009). The Dynamics of Strategy: Mastering Strategic Landscapes of the Firm. Oxford University Press. Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration
. Princeton University Press. North, M.J. and Macal, C.M. (2007). Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation. Oxford University Press.
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Loughborough University
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Introduction to Simulation Methods
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