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Multi-objective Traffic Signal Timing Optimization Using Non-dominated Sorting Genetic Algorithm II
Dazhi Sun, Rahim F. Benekohal, and S. Travis Waller
University of Illinois at Urbana-Champaign
Urbana, IL 61801, USA
{dazhisun,rbenekoh,stw}@uiuc.edu
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.
LNCS 2724, p. 2420 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003