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A multi-objective network design for real traffic models of the internet by means of a parallel framework for solving NP-hard problems

The design and optimization of a communication network is a complex task, because it involves a lot of factors. The two most important factors are the network cost and the communications delay. We have tackled this NP-hard multi-objective optimization problem using two metaheuristics not used before: NSGA-II and SPEA-II, demonstrating that SPEA-II offers better results than NSGA-II. In order to facilitate the programming tasks, we have used the PISA framework. This paper proposes also a novel PISA parallelization based on MPI that allows distributing work load between computer cluster nodes, increasing thus the productivity.