Multiobjective sparse regeneration placement algorithm in optical networks considering network performance and CAPEX

In this paper we propose the use a multiobjective evolutionary optimization algorithm to solve the regenerators placement problem. The optical network performance and the capital costs are used as optimization objectives. The blocking probability is used as the network performance indicator, which is evaluated by network simulations with an impairment aware routing and wavelength assignment algorithm, whereas the total regenerators cost is the total number of regenerators deployed in the network. Our algorithm finds which network nodes should have regeneration capability and the number of regenerators in each of these regenerating nodes. Our proposal outperformed other well known algorithms found in the literature such as NDF and SQP.