Abstract. The mallba project tackles the resolution of combinatorial optimization problems using algorithmic skeletons implemented in C ++ . mallba offers three families of generic resolution methods: exact, heuristic and hybrid. Moreover, for each resolution method, mallba provides three different implementations: sequential, parallel for local area networks, and parallel for wide area networks (currently under development). This paper shows the architecture of the mallba library, presents some of its skeletons and offers several computational results to show the viability of the approach.

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The mallba project tackles the resolution of combinatorial optimization problems using algorithmic skeletons implemented in C ++ . mallba offers three families of generic optimization techniques: exact, heuristic and hybrid. Moreover, for each technique, mallba provides three different implementations: sequential, parallel for local area networks, and parallel for wide area networks. This paper explains the architecture of the mallba library, presents some of the implemented skeletons, and offers several computational results to show the viability of the approach. In our conclusions we claim that the design used to develop the optimization techniques is general and efficient at the same time, and also that the resulting skeletons can outperforms existing algorithms on a plethora of problems.

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The Frequency Assignment Problem (FAP) is one of the key issues in the design of GSM networks (Global System for Mobile communications), and will remain important in the foreseeable future. There are many versions of FAP, most of them benchmarking-like problems. We use a formulation of FAP, developed in published work, that focuses on aspects which are relevant for real-world GSM networks. In this paper, we have designed, adapted, and evaluated several types of metaheuristic for different time ranges. After a detailed statistical study, results indicate that these metaheuristics are very appropriate for this FAP. New interference results have been obtained, that significantly improve those published in previous research.