spring 2011 - Çgie398 - lecture 51 lecture 5 : systems models and diagrams this lecture is about...
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Spring 2011 - ÇG IE398 - lecture 5 1
lecture 5 : systems models and diagrams
this lecture is about modelling
• modelling
• influence diagrams
• flow charts, precedence charts, spray diagrams etc.
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a model is• a representation of reality intended for some purpose• a representation of reality intended to be of use to
someone charged with managing or understanding that reality
• a representation of reality intended to be of use to someone in understanding, changing, managing and controlling that reality
• a representation of part of reality as seen by the people who wish to use it to understand, to change, to manage and to control that part of reality
• an external and explicit representation of part of reality as seen by the people who wish to use it to understand, to change, to manage and to control that part of reality
• a model is a tool for thinking
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a system model specifies:• the transformation processes or activities
of the system• the boundary, ie. the narrow and the wider
systems of interest• subsystems of the narrow system involved in
transformation; the dynamic relationships ie. processes; stable relationships ie. structure
• uncontrollable inputs; control inputs; decisions and decision rules
• outputs that are desired, undesired, planned, unplanned
• outputs serving as performance measures
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question is aspect affected by system variables or inputs?
does aspect affect
system?
answer YES NO
YEScomponent
or relationship
input
NO output irrelevant
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models should be:• simple but complete, not trivial or irrelevant
– simple models are easier to understand, to evaluate, to work with and to communicate
– they can be explained to problem users and owners; this helps to convince them to use models as tools for thinking (for example spreadsheets are fine)
– even if users do not understand its inner working properly, a model should be easy to manipulate and it should allow testing by owners and users
– simplicity in doing something is parsimony (Occam’s razor: the fewest possible assumptions should be made in explaining a thing ); models should observe parsimony
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• start small, then add and refine– start with a small model even if it is not
sufficiently realistic– make sure you immediately solve and test it
numerically; if data is not yet ready, use approximate data and guesstimates; this will show if the model makes sense; if it helps you to understand the problem situation
– as you discover the shortcomings of your model, refine it:• either by enriching, ie. adding new features
and components, • or by reformulating, ie. replacing with a
different, new model
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• a good model should be:– adaptive and robust so that it can be
modified when data or the problem situation changes
– appropriate to the problem situation, eg. it should allow solution within the timeframe needed
– relevant and approprite for decision making eg. without extensive need to process model outputs
– aided by diagrams such as influence diagrams– used for going back to rich pictures and mind
maps for revision of both these and the model
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influence diagrams
parameters, constraints, etc
control i/p, decision rules, etc
output
system variables: rates, levels etc
A Binfluence
rate = flow (a process element)
level = stock (a structural element)
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stocks and flows or levels and rates
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flow charts, spray diagrams etc.• flow charts are used to show logical or temporal
flows such as:– material flows– information flows– decision flows etc.
• spray diagrams are useful to map detailed cause-and-effect relationships
• precedence charts are useful in project management
• general rule for all diagrams: components of the same category ( eg. circles, squares, clouds etc.) should only show entities of the same category (eg. decisions, actions, stocks, materials etc.); do not mix categories!
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