Méthodes de décomposition et décentralisation en programmation linéaire
Partial regularization of the sum of two maximal monotone operators
Separable convexification and DCA techniques for capacity and flow assignment problems
We study a continuous version of the capacity and flow assignment problem (CFA) where the design cost is combined with an average delay measure to yield a non convex objective function coupled with multicommodity flow constraints. A separable convexification of each arc cost function is proposed to obtain approximate feasible solutions within easily computable gaps from optimality. On the other hand, DC (difference of convex functions) programming can be used to compute accurate upper bounds and...
Separable convexification and DCA techniques for capacity and flow assignment problems
We study a continuous version of the capacity and flow assignment problem (CFA) where the design cost is combined with an average delay measure to yield a non convex objective function coupled with multicommodity flow constraints. A separable convexification of each arc cost function is proposed to obtain approximate feasible solutions within easily computable gaps from optimality. On the other hand, DC (difference of convex functions) programming can be used to compute accurate upper bounds and...
Benders decomposition for local access network design with two technologies.
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