Multiperiod capacity expansion of a telecommunications connection with uncertain demand
Computers and Operations Research
A survey on benders decomposition applied to fixed-charge network design problems
Computers and Operations Research
Scenario grouping in a progressive hedging-based meta-heuristic for stochastic network design
Computers and Operations Research
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We consider a capacity-expansion problem arising in the design of telecommunication networks. The problem is to install capacity on links of the network so as to meet customer demand while minimizing total costs incurred. When studying this and related problems it is customary to assume that point-to-point demands are given. This will not bethe case in practice, however, since future demand is generally unknown and the decision must be based on uncertain forecasts. We develop a stochastic integer programming formulation of the problem and propose an L-shaped solution procedure based on well-known cutting-plane procedures for the deterministic problem. The algorithm was tested on two sets of real-life problem instances and we present results of our computational experiments.