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OPTIMIZATION OF RESOURCE DISTRIBUTION IN THE GEORGE MASON UNIVERSITY PARKING SYSTEM

This presentation discusses the problem statement, design objective, performance metrics, system design, model, results, and conclusion of the resource distribution optimization in the George Mason University parking system.

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OPTIMIZATION OF RESOURCE DISTRIBUTION IN THE GEORGE MASON UNIVERSITY PARKING SYSTEM

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  1. OPTIMIZATION OF RESOURCE DISTRIBUTION IN THE GEORGE MASON UNIVERSITY PARKING SYSTEM Stephen Cannon Ana Maria Ordoñez Alberto Mendez Vincent Vo Shakeb Rehman Amit Singh April 26, 2002

  2. Presentation Overview • Problem Statement • Design Objective • Performance Metrics • System Design • Model • Results • Conclusion

  3. Problem Statement • 42% of Faculty & Staff find parking a source of stress • 77% of Students find quality of parking poor to fair

  4. Design Objective • To increase quality of service of parking system without increasing costs.

  5. Time to Destination Shelter Safety Free Space in Parking Space Parking Space Cost Perceived Fairness Performance Metrics

  6. Performance Metrics • Collected importance weights and utility functions for each metric from a sample group of stakeholders.

  7. Baseline Design • Proposed plan by SASAKI Associates, Inc. • Plan is approved by GMU Administration • Addition of 5 parking garages in the next 20 years • Financial deficit expected up to $36 million in 2014

  8. System Design • Carpooling Incentive • Reduce Number of Cars • Reserved Space Auctions with Differential Pricing • Differentiating at Price Market Value • Better Utilization of all the Lots • Raise Revenue • Parking Space Restrictions

  9. Design Time Sequence

  10. Model: Simulation Design • Monte-Carlo simulation • 3 scenarios simulated • Do Nothing Scenario: Make no changes to present campus • Base Scenario: Only make planed changes to campus • Policy Change Scenario: Make planned changes with our policy changes

  11. Model Specifications • 5 replications • 1 sample space per 40 actual spaces (about 270 spaces) • Stakeholder’s values varied randomly • Destination varied randomly

  12. Comparison of Design Alternatives

  13. Results: Change in Revenue

  14. Conclusion • Met objective to increase quality of service of parking system without increasing costs. • Increased derived utility • Annual cost of our system is $50,000 • Annual revenue generated is $320,000

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