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Performance Comparison of Mode Choice Optimization Algorithm with Simulated Discrete Choice Modeling

机译:模拟离散选择建模的模式选择优化算法性能比较

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摘要

Until recently, a majority of modeling tasks of transportation planning, especially in discrete choice modeling, is conducted with the help of commercial software and only concerned about the result of parameter estimates to get a policy-sensitive interpretation. This common practice prevents researchers from gaining a systematic knowledge involved in estimation mechanism. In this research, to shed a light on these limited modeling practices, a standard discrete choice model's parameter is estimated using Quasi-Newton method, DFP, and BFGS. Two extended algorithms, called DFP-GSM and BFGS-GSM, are proposed for the first time to overcome the weakness of the Quasi-Newton method. The golden section method (GSM) incorporates a nonlinear programming technique to choose an optimal step size automatically. Partial derivatives of log-likelihood function are derived and coded using Visual Basic Application (VBA). Through extensive numerical evaluation, estimation capability of each proposed estimation algorithms is compared in terms of performance measures. The proposed algorithms show a stable estimation performance and the reasons were studied and discussed. Furthermore, useful insights educated in custom-built modeling are present.
机译:直到最近,运输计划的大多数建模任务,特别是在离散选择建模中,都是在商业软件的帮助下进行的,并且仅关注参数估计的结果以得到对政策敏感的解释。这种普遍的做法使研究人员无法获得涉及估计机制的系统知识。在这项研究中,为了阐明这些有限的建模实践,使用准牛顿法,DFP和BFGS估计了标准离散选择模型的参数。首次提出了两种扩展算法,分别称为DFP-GSM和BFGS-GSM,以克服拟牛顿法的缺点。黄金分割法(GSM)结合了非线性编程技术,可以自动选择最佳步长。对数似然函数的偏导数是使用Visual Basic应用程序(VBA)派生和编码的。通过广泛的数值评估,在性能指标方面比较了每种提议的估计算法的估计能力。提出的算法具有稳定的估计性能,并对其原因进行了研究和讨论。此外,还提供了在定制建模中教育的有用见解。

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  • 来源
    《Modelling and simulation in engineering》 |2018年第2018期|8169036.1-8169036.38|共38页
  • 作者单位

    Faculty of Engineering and Applied Science, Environmental Systems Engineering, University of Regina, Regina, SK, Canada S4S 0A2,City of Regina, Regina, SK, Canada S4P 3C8;

    Faculty of Engineering and Applied Science, Environmental Systems Engineering, University of Regina, Regina, SK, Canada S4S 0A2;

    Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Rajasthan 333031, India;

    Faculty of Engineering and Applied Science, Environmental Systems Engineering, University of Regina, Regina, SK, Canada S4S 0A2;

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