An efficient simulation-based optimization algorithm for large-scale transportation problems

This paper applies a computationally efficient simulation-based optimization (SO) algorithm suitable for large-scale transportation problems. The algorithm is based on a metamodel approach. The metamodel combines information from a high-resolution yet inefficient microscopic urban traffic simulator...

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Veröffentlicht in:Proceedings of the 2012 Winter Simulation Conference (WSC) S. 1 - 11
Hauptverfasser: Osorio, C., Linsen Chong
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.12.2012
Schlagworte:
Analytical models
Computational modeling
Equations
Mathematical model
Optimization
Queueing analysis
Transportation
ISBN:1467347795, 9781467347792
ISSN:0891-7736
Online-Zugang:Volltext
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Zusammenfassung:This paper applies a computationally efficient simulation-based optimization (SO) algorithm suitable for large-scale transportation problems. The algorithm is based on a metamodel approach. The metamodel combines information from a high-resolution yet inefficient microscopic urban traffic simulator with information from a scalable and tractable analytical macroscopic traffic model. We then embed the model within a derivative-free trust region algorithm. We evaluate its performance considering tight computational budgets. We illustrate the efficiency of this algorithm by addressing an urban traffic signal control problem for the full city of Lausanne, Switzerland. The problem consists of a nonlinear objective function with nonlinear constraints. The problem addressed is considered large-scale and complex both in the fields of derivative-free optimization and simulation-based optimization. We compare the performance of the method to a traditional metamodel method.
ISBN:1467347795
9781467347792
ISSN:0891-7736
DOI:10.1109/WSC.2012.6465156