We present a class of problems that arise in the design of the Next Generation Access Networks. The main features of these networks are: to be based on fiber links of relatively long length with respect to traditional copper based networks, users may be reached directly by fibers, and the presence of few central offices managing a large number of users. We present an Integer Programming model that captures the technological constraints and the deployment costs. The model serves as a basis for a decision support tool in the design of the Next Generation Access Networks. Pure Integer Programming cannot handle real-life problem instances, giving rise to new challenges and opportunities for hybrid Constraint Programming-Mathematical Programming methods. In this paper, we compare a LP-based randomized rounding algorithm with a Constraint-based Local Search formulation. The use of an LP relaxation is twofold: it gives lower bounds to the optimal solution, and it is easily embedded into a randomized rounding algorithm. The Constraint-based Local Search algorithm is then exploited to explore the set of feasible solutions. With these algorithms we are able to solve real-life instances for one of the problems presented in this paper. © 2010 Springer-Verlag.
On the Design of the Next Generation Access Networks
Gualandi, Stefano
;Malucelli, Federico;
2010-01-01
Abstract
We present a class of problems that arise in the design of the Next Generation Access Networks. The main features of these networks are: to be based on fiber links of relatively long length with respect to traditional copper based networks, users may be reached directly by fibers, and the presence of few central offices managing a large number of users. We present an Integer Programming model that captures the technological constraints and the deployment costs. The model serves as a basis for a decision support tool in the design of the Next Generation Access Networks. Pure Integer Programming cannot handle real-life problem instances, giving rise to new challenges and opportunities for hybrid Constraint Programming-Mathematical Programming methods. In this paper, we compare a LP-based randomized rounding algorithm with a Constraint-based Local Search formulation. The use of an LP relaxation is twofold: it gives lower bounds to the optimal solution, and it is easily embedded into a randomized rounding algorithm. The Constraint-based Local Search algorithm is then exploited to explore the set of feasible solutions. With these algorithms we are able to solve real-life instances for one of the problems presented in this paper. © 2010 Springer-Verlag.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.