A dynamic programming algorithm for the local access network expansion problem

Technological innovations and growing consumer demand have led to a variety of design and expansion problems in telecommunication networks. In particular, local access net- works have received a lot of attention, since they account for approximately 60% of total investments in communication facilities. In this paper we consider the Local Access Network Expansion Problem, in which growing demand can be satisfied by expanding cable capacities and/or installing concentrators in the network. The problem is known to be NP-hard. We present a pseudo-polynomial dynamic programming algorithm, with time complexity O( nB²) and storage requirements O( nB ), where n refers to the size of the network, and B to an upper bound on concentrator capacity. The cost structure in the network is assumed to be decomposable, but may be non-convex, non-concave, and node and edge dependent otherwise. Computational results indicate that the algorithm is very efficient and can solve medium to large scale problems to optimality within (fractions of) seconds to minutes.mathematical economics and econometrics ;

A Dynamic Programming Algorithm for the ATM Network Installation Problem on a Tree

This paper considers the ATM Network Installation Problem on a tree. To install sucha communication network, decisions concerning the location of hardware devices, the capacity installation on links, and the routing of demands have to be made simultaneously. The problem is shown to be NP-hard. By exploiting the tree structure we show that the problem can be solved to optimality using a pseudo-polynomial time dynamic programming algorithm. Computational experiments on real-life problem instances indicate that the algorithm is highly e#cient. 1 Introduction Modern telecommunication networks are capable of processing multiple telecommunication services on a single physical network. These so-called broadband networks usually consist of several hierarchical network layers. At the top layer #often referred to as the Backbone#, large capacity nodes serve large geographical areas. These areas are decomposed into smaller regions, eachof which is served by nodes located in lower layers of the ne..