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Multi-objective Traffic Signal Timing Optimization Using Non-dominated Sorting Genetic Algorithm II

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Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2724))

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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.

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© 2003 Springer-Verlag Berlin Heidelberg

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Sun, D., Benekohal, R.F., Waller, S.T. (2003). Multi-objective Traffic Signal Timing Optimization Using Non-dominated Sorting Genetic Algorithm II. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_143

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  • DOI: https://doi.org/10.1007/3-540-45110-2_143

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40603-7

  • Online ISBN: 978-3-540-45110-5

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