Fuzzy Optimization Approach: Comparison with the Classical Optimization Method Using the Problem of Timing a Traffic Signal

The fuzzy optimization approach is known to be useful for multiobjective and multiconstraint decision situations in which the objectives and constraints are approximate. Although many transportation problems are in this category, the actual application of fuzzy optimization has been rare so far. This paper introduces the fuzzy optimization technique and tests this approach by applying it to setting the signal timing, in which the values of the parameters are not well defined. Three existing signal-timing models are reformulated into the fuzzy optimization approach to accommodate the uncertainty in the parameter values of the models. The results are compared with those obtained from the traditional formulation of the three models. The models tested are the "Highway Capacity Manual" approach, Webster’s method, and Akcelik’s method. For average delay and fuel consumption in general, the results obtained from the fuzzy optimization approach are found to be smaller than those obtained using the traditional approach of the three models. This study finds that the fuzzy optimization approach can be useful for transportation problems when objectives and constraints are many, when the boundary values of the constraints are not well defined, and when the goodness of the solution is based on acceptability or best compromise.

• Record URL:
  https://doi.org/10.3141/2024-10
• 
• Summary URL:
  http://scholar.google.com/scholar_lookup?title=Fuzzy+Optimization+Approach%3a+Comparison+with+the+Classical+Optimization+Method+Using+the+Problem+of+Timing+a+Traffic+Signal&author=Y.+Murat&author=S.+Kikuchi&publication_year=2007
• Availability:
  • Find a library where document is available. Order URL: http://www.trb.org/Main/Public/Blurbs/159707.aspx
• Authors:
  • Murat, Yetis Sazi
  • Kikuchi, Shinya
• Publication Date: 2007

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 82-91
• Monograph Title: Information Technology, Geographic Information Systems, and Artificial Intelligence
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Issue Number: 2024
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Boundary value problems; Constraints; Fuel consumption; Optimization; Traffic delays; Traffic signal timing; Uncertainty
• Uncontrolled Terms: Fuzzy optimization
• Subject Areas: Energy; Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01043547
• Record Type: Publication
• ISBN: 9780309104517
• Files: TRIS, TRB, ATRI
• Created Date: Feb 8 2007 5:32PM