Multi-objective traffic signal timing optimization using non-dominated sorting genetic algorithm II

Dazhi Sun, Rahim F. Benekohal, S. Travis Waller

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper presents the application of Non-dominated Sorting Genetic Algorithm II (NSGA II) in solving multiple-objective signal timing optimization problem (MOSTOP). Some recent researches on intersection signal timing design optimization and multi-objective evolutionary algorithms are summarized. NSGA II, which can find more of the Pareto Frontiers and maintain the diversity of the population, is applied to solve three signal timing optimization problems with 2-objective and 3-constraint, which account for both deterministic and stochastic traffic patterns. Mathematical approximation of the resulting Pareto Frontiers are developed to provide more insight into the trade-off between different objectives. GAs experimental design and result analysis are presented with some recommendations for prospective applications.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsErick Cantú-Paz, James A. Foster, Graham Kendall, Mark Harman, Dipankar Dasgupta, Kalyanmoy Deb, Lawrence David Davis, Rajkumar Roy, Una-May O'Reilly, Hans-Georg Beyer, Russell Standish, Stewart Wilson, Joachim Wegener, Mitch A. Potter, Alan C. Schultz, Kathryn A. Dowsland, Natasha Jonoska, Julian Miller
PublisherSpringer-Verlag Berlin Heidelberg
Pages2420-2421
Number of pages2
ISBN (Print)3540406034, 9783540406037
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2724
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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