Presentation / Talk

Choice set generation for iterated DTA simulations

We apply the Metropolis-Hastings algorithm to efficiently sample from arbitrary paths distributions in a general network. Paths can be generalized into all-day travel plans through, e.g., an appropriate network expansion. The Metropolis-Hastings algorithm creates a Markov chain of paths, which resembles DTA simulations that can also be phrased as Markov chains. A combination of both chains could lead to better understood DTA simulations that avoid the arbitrariness of current choice set generation procedures.


    • EPFL-TALK-167461

    Record created on 2011-07-06, modified on 2017-02-16

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