Transportation Economics/Systems
From Wikibooks, the open-content textbooks collection
Systems
"All Models are Wrong, Some Models are Less Wrong than Others" -- Anonymous
"All Models are Wrong, Some Models are Useful" -- George Box [1]
Contents |
[edit] Models vs. Frameworks
Model - Mathematical Representation of a System
Framework - Qualitative Organizing Principle for Analyzing System
[edit] Frameworks
[edit] Example: Porter’s Diamond of Advantage
Michael Porter proposes four key determinants of competitiveness, which he calls the "Diamond of Advantage," based on cases from around the world:
- factor conditions, such as a specialized labor pool, specialized infrastructure and sometimes selective disadvantages that drive innovation;
- home demand, or local customers who push companies to innovate, especially if their tastes or needs anticipate global demand;
- 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
- 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.
[edit] Why Model
- gain insight into complex situations by understanding simpler situations resembling them
- optimization
- system operation
- earn from model building process
- modeling as negotiation tool
[edit] The issue of viewpoint
[edit] 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”.
[edit] Point of View
Who are the results for?
Subjective advocacy vs. objective analysis
[edit] 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.
To name but a few ...
[edit] Modeling Decisions
[edit] Organization
- Hierarchy of Models
- Centralized vs. Decentralized (Optimization (Global) vs. Agent, Local Optimization)
[edit] Time
- Time Frame
- Static vs. Dynamic
- Real Time vs. Offline
- Short Term vs. Long Term (Partial vs. General Equilibrium)
- Proactive vs. Reactive (Predictive vs. Responsive)
[edit] Space
- Scale/Detail
- Spatial Extent
- Boundaries (Boundary Effects)
- Macroscopic vs. Microscopic (Zones, Flows vs. Individuals, Vehicles)
[edit] Process
- Stochastic vs. Deterministic
- Linear vs. Nonlinear
- Continuous vs. Discrete
- Numerical Simulation vs. Closed Form Solution
- Equilibrium vs. Disequilibrium
[edit] Type
- Behavioral vs. Aggregate Model
- Physical vs. Mathematical Models
[edit] Solution Techniques
Understanding the System
Approximations and Speed in Optimization (Local Optima) vs. Certainty (Brute Force, Global Optima)
[edit] 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
[edit] Problem PRT: Skyweb Express
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 should be used. Why?
2. What data should be collected.
Form groups of 3 and take 15 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.
[edit] Land Growth as a System
[edit] Supply and Demand as a Feedback System
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.
[edit] 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
[edit] Summary
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. 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). 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.
