Models and Frameworks

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Models and Frameworks

• David Levinson

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ALL MODELS ARE WRONG, SOME MODELS ARE LESS WRONG
THAN OTHERS.

• Some Models are Useful

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• Model - Mathematical Representation of a System
• Framework - Qualitative Organizing Principle for
  Analyzing System

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Frameworks
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Diamond of Advantage
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Example Porters Diamond

• Michael Porter proposes four key determinants of
  competitiveness, which he calls the "Diamond of
  Advantage," based on cases from around the world
  
• 1. factor conditions, such as a specialized labor
  pool, specialized infrastructure and sometimes
  selective disadvantages that drive innovation
• 2. home demand, or local customers who push
  companies to innovate, especially if their tastes
  or needs anticipate global demand
• 3. related and supporting industries,
  specifically internationally competitive local
  supplier industries, creating a high quality,
  supportive business infrastructure, and spurring
  innovation and spin-off industries and
• 4. industry strategy/rivalry, involving both
  intense local rivalry among area industries that
  is more motivating than foreign competition and
  as well as a local "culture" which influences
  individual industries' attitudes toward
  innovation and competition.

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Why Model

• gain insight into complex situations by
  understanding simpler situations resembling them
• optimization
• system operation
• learn from model building process
• modeling as negotiation tool

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Modeling Shapes Your Worldview, And Vice Versa

• What is a worldview?
• Your outlook on life, and the world
• Your internal model of how the world works (I.e.
  what do you expect, what is a surprise)
• The result of Where you stand depends on where
  you sit
• Point of View
• Who are the results for?
• Subjective advocacy vs. objective analysis

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Types of Models

• Network analysis
• Linear Programming
• Nonlinear Programming
• Simulation
• Deterministic queuing
• Probabilistic queuing
• Regression
• Neural Nets
• Genetic Algorithm
• Cost/ Benefit Analysis
• Life-cycle costing

• System Dynamics
• Control Theory
• Difference Equations
• Differential Equations
• Probabilistic Risk Assessment
• Supply/Demand Equilibrium
• Game Theory
• Statistical Decision Theory
• Markov Models
• Cellular Automata
• Etc.

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Modeling Decisions

• Hierarchy of Models
• Scale/Detail
• Time Frame
• Spatial Extent
• Boundaries (Boundary Effects)
• Macroscopic vs. Microscopic (Zones, Flows vs.
  Individuals, Vehicles)
• Static vs. Dynamic
• Stochastic vs. Deterministic
• Linear vs. Nonlinear
• Continuous vs. Discrete
• Numerical Simulation vs. Closed Form Solution

• Behavioral vs. Aggregate Model
• Physical vs. Mathematical Models
• Real Time vs. Offline
• Short Term vs. Long Term (Partial vs. General
  Equilibrium)
• Proactive vs. Reactive (Predictive vs.
  Responsive)
• Centralized vs. Decentralized (Optimization
  (Global) vs. Agent, Local Optimization)
• Equilibrium vs. Disequilibrium

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Solution Techniques

• Understanding the System
• Approximations and Speed in Optimization (Local
  Optima) vs. Certainty (Brute Force, Global
  Optima)

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Tradeoffs (Time and resource constraints)

• Money,
• Data,
• Computation,
• Labor,
• Ease of Use,
• Convincing (e.g. Graphic Displays),
• Extendable,
• Evidence of Model Benefits,
• Measuring Model Success

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PRT Skyweb Express
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PROBLEM

• The Metropolitan Council of Governments (the
  region's main transportation planning agency) is
  examining whether the Twin Cities should build a
  new Personal Rapid Transit system in downtown
  Minneapolis, and they have asked you to recommend
  how it should be analyzed
• 1. What kind of model(s) should be used. Why?
• 2. What data should be collected.
• Form groups of 3 and take 10 minutes and think
  about what kinds of models you want to run and
  what data you want to collect, what questions you
  would ask, and how it should be collected. Each
  group should have a note-taker, but all members
  of the group should be able to present findings
  to the class.
• DISCUSS

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Land Growth as a System
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Some History

• A. World War II
• i. deployment of radar in a coordinated way
• ii. spread to other fields such as fighter
  tactics, mission planning and weapons evaluation.
• iii. use of mathematical techniques in such
  problems came to be known as operations research,
  other statistical and econometric techniques are
  being applied

• B. Post World War II
• i. techniques spread to universities.
  Mathematical development and application to a
  broad variety of problems.
• ii. development of systems analysis. Same
  analytical framework but to more complex problems
  for existing mathematical techniques were not
  adequate.

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Some Definitions

• "A coordinated set of procedures which addresses
  the fundamental issues of design and management
  that of specifying how men, money and materials
  should be combined to achieve a higher purpose"
  De Neufville
• "... primarily a methodology, a philosophical
  approach to solving problems for and for
  planning innovative advances" Baker
• "Professionals who endeavor to analyze
  systematically the choices available to public
  and private agencies in making changes in the
  transportation system and services in a
  particular region" Manheim
• "Systems analysis is not easy to write about
  brief, one sentence definitions frequently are
  trivial" Thomas

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The Rational Planning Process
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Rational Planning Redux
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Step A. Define the System

• i. objectives - measures the effectiveness or
  performance
• ii. environment - things which affect the system
  but are not affected by it
• iii. resources - factor inputs to do the work
• iv. components - set of activities or tasks of
  the system
• v. management - sets goals, allocates resources
  and exercises control over components
• vi. model of how variables in 1-5 relate to each
  other

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Step B Generate and assess alternatives
available to management

• 1. algorithms-systematic search over available
  alternatives
• analytical
• exact numerical
• heuristic numerical
• 2. generate alternatives selectively, evaluate
  subjectively
• fatal flaw analysis
• simple rating schemes
• Delphi exercises
• 3. generate alternatives judgmentally, evaluate
  scientifically using system model
• 4. need for "stopping rule"

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Step C Choose alternatives

• The analyst is generally not the decision maker.
  The actual influence of the results of the
  analysis in actual decisions will depend on
• determinacy of evaluation
• confidence in the results on the part of the
  decision maker
• consistency of rating among alternatives

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Step D Implementation

• Just Do It.

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Step E Evaluation

• 1. definition output from a later step in
  systems analysis used as input to a later step.
• 2. Examples.
• analysis leads to revisions in systems definition
• implementation experience leads to a revision of
  output system definition or values that underlay
  that definition.

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Is the Rational Planning process Rational?

• Discuss in pairs for ten minutes, be prepared to
  discuss in class

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Some Issues

• Limited Computational or Solution Generating
  Capacity
• Incomplete Information
• Cost of Analysis
• Conflicting Goals/Evaluation Criteria
• Reliance on Experts (What about the People?)

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Alternative Planning Decision Making Paradigms.
Are They Irrational?

• Satisficing
• Incrementalist
• Organizational Process
• Poltical Bargaining
• Decomposition/Hierarchical Strategy/Tactics/Operat
  ions

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Summary

• 1. Applied systems analysis is the use of
  rigorous methods to assist in determining optimal
  plans, designs and solutions to large scale
  problems through the application of analytical
  methods.
• 2. Applied systems analysis focuses upon the use
  of methods, concepts and relationships between
  problems and the range of techniques available.
  Any problem can have multiple solutions. The
  optimal solution with depend upon technical
  feasibility (engineering) and costs and valuation
  (economics).
• 3. Applied systems analysis is an attempt to move
  away from the engineering practice of design
  detail and to integrate feasible engineering
  solutions with desirable economic solutions. The
  systems designer faces the same problem as the
  economist, "efficient resource allocation" for a
  given objective function.

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