2008
DOI: 10.3141/2085-02
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Simultaneous Perturbation Stochastic Approximation Algorithm for Solving Stochastic Problems of Transportation Network Analysis

Abstract: Stochastic optimization has become one of the important modeling approaches in transportation network analysis. For example, for traffic assignment problems based on stochastic simulation, it is necessary to use a mathematical algorithm that iteratively seeks out the optimal, the suboptimal solution, or both, because an analytical (closed-form) objective function is not available. Therefore, efficient stochastic approximation algorithms that can find optimal or suboptimal solutions to these problems are needed… Show more

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Cited by 6 publications
(3 citation statements)
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“…Despite the SPSA-based traffic signal timing patent filed by Spall in 1995 [12], SPSA is receiving little if any attention by signal timing practitioners and product vendors. SPSA is rated highly by researchers of traffic demand matrices [13], traffic assignment [14], and traffic model calibration [15]. SPSA has been lauded by transportation researchers "for its proven performance and computational properties in large-scale problems" [16], and for its ability to "solve very large noisy problems in a computationally attractive fashion" [17].…”
Section: Problem Statementmentioning
confidence: 99%
“…Despite the SPSA-based traffic signal timing patent filed by Spall in 1995 [12], SPSA is receiving little if any attention by signal timing practitioners and product vendors. SPSA is rated highly by researchers of traffic demand matrices [13], traffic assignment [14], and traffic model calibration [15]. SPSA has been lauded by transportation researchers "for its proven performance and computational properties in large-scale problems" [16], and for its ability to "solve very large noisy problems in a computationally attractive fashion" [17].…”
Section: Problem Statementmentioning
confidence: 99%
“…The proposed calibration methodology is based on the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm [13,14], which has been proposed in the past for the calibration of microscopic traffic flow simulation models [11,12,[15][16][17][18]. Vehicular traffic systems modeled using microscopic traffic flow simulation models typically are characterized by a large number of parameters and stochasticities.…”
Section: Introductionmentioning
confidence: 99%
“…The LM algorithm is a good choice for comparison with SPSA, as it appears to be the fastest method (up to ten to one hundred times faster than the standard back-propagation algorithms) for training moderate-sized feed forward neural networks. SPSA, on the other hand, has been successfully implemented for optimization in transportation network analysis problems (Ozguven and Ozbay, 2008). In the following subsections, we will show the comparative results of the proposed online control methodology based on these algorithms, namely the neural network approximation with Levenberg-Marquardt (LM) algorithm and SPSA algorithm.…”
Section: Simultaneous Perturbation Stochastic Approximation (Spsa) Mementioning
confidence: 99%