In this work we consider the network equilibrium problem formulated as convex minimization problem whose variables are the path flows. In order to take into account the difficulties related to the large dimension of real network problems we adopt a decomposition-based approach suitably combined with a column generation strategy. We present an inexact block-coordinate descent method and we prove the global convergence of the algorithm. The results of computational experiments performed on medium-large dimensional problems show that the proposed algorithm is at least competitive with state of the art algorithms.

A convergent and efficient decomposition method for the traffic assignment problem / Di Lorenzo, D.; Galligari, A.; Sciandrone, M.. - In: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS. - ISSN 0926-6003. - 60:1(2015), pp. 151-170. [10.1007/s10589-014-9668-6]

A convergent and efficient decomposition method for the traffic assignment problem

Sciandrone M.
2015

Abstract

In this work we consider the network equilibrium problem formulated as convex minimization problem whose variables are the path flows. In order to take into account the difficulties related to the large dimension of real network problems we adopt a decomposition-based approach suitably combined with a column generation strategy. We present an inexact block-coordinate descent method and we prove the global convergence of the algorithm. The results of computational experiments performed on medium-large dimensional problems show that the proposed algorithm is at least competitive with state of the art algorithms.
2015
Column generation; Cyclic block-coordinate methods; Decomposition methods; Network equilibrium
01 Pubblicazione su rivista::01a Articolo in rivista
A convergent and efficient decomposition method for the traffic assignment problem / Di Lorenzo, D.; Galligari, A.; Sciandrone, M.. - In: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS. - ISSN 0926-6003. - 60:1(2015), pp. 151-170. [10.1007/s10589-014-9668-6]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1625737
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