2015
DOI: 10.1016/j.trc.2014.11.006
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An enhanced SPSA algorithm for the calibration of Dynamic Traffic Assignment models

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Cited by 124 publications
(80 citation statements)
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“…Finally, a third research line, which refers to the contents analyzed in this paper, concerns the structure of the objective function and specifically the investigation of the performances of SPSA AD-PI solution method when applied to the vector formulation recently introduced by Lu et al [12], which showed to improve the efficiency of traditional SPSA method significantly.…”
Section: Conclusion and Further Researchmentioning
confidence: 99%
See 1 more Smart Citation
“…Finally, a third research line, which refers to the contents analyzed in this paper, concerns the structure of the objective function and specifically the investigation of the performances of SPSA AD-PI solution method when applied to the vector formulation recently introduced by Lu et al [12], which showed to improve the efficiency of traditional SPSA method significantly.…”
Section: Conclusion and Further Researchmentioning
confidence: 99%
“…In addition, they proposed an adaptive approach that computes, at each iteration, the weights in the gradient computation according to the relevance of any O-D pair as computed. Lu et al [12] introduced an enhanced SPSA algorithm, which incorporates spatial and temporal correlation between parameters and measurements to minimize the noise generated by uncorrelated measurements and reduce the gradient approximation error. While in the original SPSA the objective function is a single scalar, in the weighted SPSA it is a vector, whose gradient components are weighed by a matrix that expresses the correlations between parameters and measurements.…”
Section: Introductionmentioning
confidence: 99%
“…The first-order SPSA (1SPSA) is related to the KieferWolfowitz (K-W) stochastic approximation (SA) method (Spall, 1992), whereas the second-order SPSA (2SPSA) is a stochastic analogue of the deterministic Newton-Raphson algorithm (Spall, 2000). Lu et al (2015) and Antoniou et al (2015) proposed an enhanced SPSA algorithm for large-scale dynamic traffic assignment applications, called Weighted SPSA (W-SPSA), which incorporates the information of spatial and temporal correlation in a traffic network to limit the impact of noise and improve convergence and robustness. Tymbakianaki et al (2015) proposed the c-SPSA algorithm, a modification which applies the simultaneous perturbation approximation of the gradient within a small number of carefully constructed "homogeneous" clusters one at a time, as opposed to all elements at once.…”
Section: Simultaneous Perturbation Stochastic Approximation (Spsa)mentioning
confidence: 99%
“…However, no significant improvement was made (Lu, 2014). This led us to believe that SPSA itself has fundamental limitations, when applied to very large scale, noisy problems without analytical representation and with correlated parameters and measurements, as identified in Lu et al (2015); Cipriani et al (2011);Cantelmo et al (2014). One of those limitations refers to the agnostic perspective on the correlation structure between the variables involved and the observations.…”
Section: Introductionmentioning
confidence: 99%
“…The proposal of Weighted SPSA (W-SPSA) from Lu et al (2015) aims precisely to overcome these limitations by relying on a weight matrix, W, that represents the appropriate correlation structure. While the authors demonstrated the concept and successfully compared it with SPSA in several settings, the treatment of the essential ingredient (i.e.…”
Section: Introductionmentioning
confidence: 99%