A Golden Ratio-Based Genetic Algorithm and Its Application in Traffic Signal Timing Optimization for Urban Signalized Intersections

Yang, Wenchen; Zhang, Lun; Zhang, Lei; Shi, Hongyun

doi:10.1061/9780784413159.004

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…A golden ratio-based heuristic genetic algorithm (GRGA) has been proposed to yield approximate solutions for expanded capacities of urban road network [ 14 ]. The proposed heuristic is able to find the closest solution to the best solution by introducing golden ratio (GR) to enhance the local optimal capability of an improved real-coded genetic algorithm [ 15 ].…”

Section: Solution Algorithmmentioning

confidence: 99%

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

Zhang

Yang

et al. 2015

Computational Intelligence and Neuroscience

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This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity.

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Section: Solution Algorithmmentioning

confidence: 99%

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

Zhang

Yang

et al. 2015

Computational Intelligence and Neuroscience

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“…This objectively makes the system which works well in foreign countries don't have desired control results after displaced to domestic. Especially in the peaking commuting, non-vehicle became the main factor to effect junction (Ma and Yang, 2010;Zhang et al, 2004;Wang et al, 2006). Then, it is not suitable to adopt F•Webster B•Curb for traffic signal timing directly in our country.…”

Section: Introductionmentioning

confidence: 98%

Research on Bus Priority Signal Planning Under Mixed Traffic Flow

Yu¹,

Cao²,

Wu³

et al. 2013

RJASET

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This study, based on principle of bus priority, uses complementary doctrines to create mixed traffic flow intersection signal-planning model under effective green time. By discussing the objective function of optimization model, we ensure and take advantage of nonlinear equivalence feature. After that, this study refers to Newton algorithm to solve this model. Considering the mixed characteristic of traffic flow, we put forward to adoption of traffic capacity, delay time and parking number together to evaluate operation effect. Through the example analysis, it was shown that this model and solution algorithm responded well and indications increased remarkably.

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“…-If m = k + 1, e = s = 1 and k = 3, we have new sequences derived from our generalized equation (33) whose two consecutive terms converge to lim an a n−1 .…”

Section: The Limit Of the Sequence Is Independent Of The Initial Condmentioning

confidence: 99%

“…-Face detection evaluation [1] -Fashion and textile design [2,3,30] -Analog-to-digital converter design [31,32] -Traffic signal timing optimization [33] -Heart and perception based biometrics [34,35,36] -Audio and speech sampling [37,38] -Barcode generation [39] The Golden ratio was first referenced by Euclid (300 B.C.) in his book "The Elements" [4,40,41].…”

Section: Introductionmentioning

confidence: 99%

The Extended Golden Section and Time Series Analysis

Agaian¹,

Gill²

2017

FSP

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The Golden ratio has played an important role in musical composition, architecture, visual art, science, and increasingly in signal processing [1,2,3]. Underlying many of these applications are several extensions of the golden proportions including the Golden p-Section by Stakhov, the generalized Golden section by Bradley, and others [4,5]. In this paper we review and introduce generalizations of the Golden ratio. We show that there exists a fundamental connection between the limit of two consecutive terms of recursive sequences, the generalized (p, q)-Golden ratio and the Golden ratio generated by the characteristic equation. We apply these generalizations to forecasting financial time series to illustrate one of their applications in signal processing.

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A Golden Ratio-Based Genetic Algorithm and Its Application in Traffic Signal Timing Optimization for Urban Signalized Intersections

Cited by 6 publications

References 3 publications

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

Research on Bus Priority Signal Planning Under Mixed Traffic Flow

The Extended Golden Section and Time Series Analysis

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