Development of a stochastic genetic algorithm for traffic signal timings optimization

Ahmed A. Ezzat, Hala A. Farouk, Khaled S. El-Kilany, Ahmed F. Abdelmoneim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Traffic Management of over-saturated urban networks is a great challenge in large metropolitan areas. Over-saturation is a severe traffic condition when excessive unbalance between the vehicular demand and the road network's capacity takes place, generating serious inflation of queuing lengths, waiting times, spillbacks and risk of accidents. Other environmental, psychological and economic aspects could also be related to the problem. However, adequate traffic management can successfully handle the demand in both space and time, and overcome the arising congestion dilemma. A mathematical model representing the traffic control stochastic environment has been developed. The optimum/near-optimum traffic signal timing values have been determined through the application of a genetic algorithm that feeds these values into a developed simulation model to obtain the corresponding queuing parameters. The generated signal timings significantly enhance the traffic performance and alleviate the choke points over a multiple-junction urban network. The developed approach has been applied on a network consisting of two consecutive junctions in Alexandria, Egypt using actual field data. Although the solution has not been implemented in reality; nevertheless, optimization results are very promising and show that the proposed model can drastically improve the queuing parameters of the vehicular flow.

Original languageEnglish (US)
Title of host publicationIIE Annual Conference and Expo 2014
PublisherInstitute of Industrial Engineers
Number of pages10
ISBN (Electronic)9780983762430
StatePublished - 2014
Externally publishedYes
EventIIE Annual Conference and Expo 2014 - Montreal, Canada
Duration: May 31 2014Jun 3 2014

Publication series

NameIIE Annual Conference and Expo 2014


OtherIIE Annual Conference and Expo 2014

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Control and Systems Engineering


  • Genetic Algorithms
  • Mathematical Modeling
  • Modeling and Simulation
  • Traffic Management


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