New solution algorithms for asymmetric traffic assignment model

Huey Kuo Chen, Chung Yung Wang, David E. Boyce

Research output: Contribution to journalArticlepeer-review

Abstract

The asymmetric traffic assignment model can improve the traditional traffic assignment model by adopting detailed network representation and more realistic asymmetric cost functions. The diagonalization, streamlined diagonalization, and projection methods are three widely mentioned solution algorithms for solving asymmetric traffic assignment models. The diagonalization and streamlined diagonalization methods have the advantage of requiring less computer memory but typically require greater computational time. The projection method has the advantage of convening more rapidly but requires a large computer memory. In order to balance computer memory and computational time, we propose two new algorithms; i.e., hybrid and streamlined hybrid methods. According to our case study, the proposed algorithms show their superiority over the diagonalization and streamlined diagonalization methods in terms of computational time, and over the projection method in terms of computer memory Both new algorithms can handle small or medium networks sized asymmetric traffic assignment problems on personal computers.

Keywords

  • Asymmetric traffic assignment
  • Contraction operator
  • Diagonalization
  • Hybrid
  • Multicommodity flow problem
  • Projection

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