A performance comparison of multi-objective optimization evolutionary algorithms for all-optical networks design

In this paper we investigate the performance of well known multi-objective optimization evolutionary algorithms (MOEA) applied to the design of all-optical networks. We focused on the simultaneous optimization of the network topology and the device specifications in order to both minimize the total cost to build the network, i.e. the capital expenditure, and to maximize the overall network performance. We used the network blocking probability to assess the quality of the network service. We have considered the following five different MOEA: NSGAII, SPEA2, PESAII, PAES and MODE. In order to suggest a suitable algorithm to solve the problem, we performed a set of simulations aiming to analyze the convergence ability and the diversity of the generated solutions. We used four well known metrics to compare the achieved Pareto Fronts: hypervolume, spacing, maximum spread and coverage. From our results, we believe that the NSGAII and the SPEA2 algorithms are more suitable to solve this specific problem.