Application of genetic algorithms to generate optimum signal coordination for congested networks

Montty Girianna, Rahim F Benekohal

Research output: Contribution to conferencePaper

Abstract

This paper presents two different Genetic Algorithms (GA) applied to design signal coordination for oversaturated networks. Signal coordination is formulated as a dynamic optimization problem and is solved using GA for the entire duration of congestion. This paper considers a tradeoff between simple GA (SGA), which requires a large population converging in a single convergence epoch, and micro GA (MGA), which requires smaller population with multiple epochs. A comparison is made for given resources available, that is, a fixed number of function evaluations. To provide quality solutions, SGA requires a large population but takes a longer time to converge, and thus it is not efficient for a real-time system. MGA overcomes the drawback encountered by SGA, that is, the time penalty involved in evaluating the fitness values for a large population. This paper reveals that MGA implementation on signal coordination problems reaches the near-optimal region of signal timing much earlier than SGA implementation. For a given number of functional evaluations, a small population size of MGA outperforms SGA executed with a larger population size.

Original languageEnglish (US)
Pages762-769
Number of pages8
StatePublished - Jan 1 2002
EventProceedings of the seventh International Conference on: Applications of Advanced Technology in Transportation - Cambridge, MA, United States
Duration: Aug 5 2002Aug 7 2002

Other

OtherProceedings of the seventh International Conference on: Applications of Advanced Technology in Transportation
CountryUnited States
CityCambridge, MA
Period8/5/028/7/02

    Fingerprint

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Girianna, M., & Benekohal, R. F. (2002). Application of genetic algorithms to generate optimum signal coordination for congested networks. 762-769. Paper presented at Proceedings of the seventh International Conference on: Applications of Advanced Technology in Transportation, Cambridge, MA, United States.