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Communication Dans Un Congrès Année : 2022

Exploring accelerated evolutionary parameter search for iterative large-scale transport simulations in a new calibration testbed

Sebastian Hörl

Résumé

Large-scale agent-based transport models of whole territories have become an important tool in research and planning of new services and policies. Yet, studies based on those tools are rarely reproducible due to the complexity of data sources and modeling processes. One important element towards fully replicable simulations is automatic calibration of behavioral and infrastructural model parameters. The present paper contributes to standardizing the calibration process by describing a consistent framework for benchmarking calibration objectives and optimization algorithms. Furthermore, the paper advances the current state of the art by exploring the integration of a search acceleration method for iterative simulators (opdyts) with sample-based evolutionary search algorithms. In a use case for Paris and the MATSim simulator, we demonstrate the applicability of the framework. We show that opdyts accelerates the parameter search process, although its comparative runtime benefits decrease with higher availability of computational resources.
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Dates et versions

hal-03676897 , version 1 (24-05-2022)

Identifiants

  • HAL Id : hal-03676897 , version 1

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Sebastian Hörl. Exploring accelerated evolutionary parameter search for iterative large-scale transport simulations in a new calibration testbed. 10th symposium of the European Association for Research in Transportation( hEART 2022 ), Jun 2022, Leuven, Belgium. ⟨hal-03676897⟩
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