Abstract
The efficiency of the network flow techniques can be exploited in the solution of nonlinearly constrained network flow problems by means of approximate sub-gradient methods. In particular, we consider the case where the side constraints (non-network constraints) are convex. We propose to solve the dual problem by using ε-subgradient methods given that the dual function is estimated by minimizing approximately a Lagrangian function with only network constraints. Such Lagrangian function includes the side constraints. In order to evaluate the efficiency of these ε-subgradient methods some of them have been implemented and their performance computationally compared with that of other well-known codes. The results are encouraging.
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Mijangos, E. (2006). On the Efficiency of the ε-Subgradient Methods Over Nonlinearly Constrained Networks. In: Ceragioli, F., Dontchev, A., Futura, H., Marti, K., Pandolfi, L. (eds) System Modeling and Optimization. CSMO 2005. IFIP International Federation for Information Processing, vol 199. Springer, Boston, MA. https://doi.org/10.1007/0-387-33006-2_10
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DOI: https://doi.org/10.1007/0-387-33006-2_10
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