Iterated harmony differential search for the minimum interference frequency assignment problem

The Minimum Interference Frequency Assignment Problem (MI-FAP) requires the assignment of frequencies to every transceivers of the network. Subject to separation constraints among frequencies assigned to some transceivers, the assignment is managed in such a way as to take account of these constraints. This problem is a famous challenging NP-Hard combinatorial optimization problem for which the metaheuristics offered and continue to offer a good alternative to solve it. In this work we are interesting in developing an iterated collaborative metaheuristic that combines a Differential Evolution (DE) and a Harmony Search (HS) with an adaptive restart. Computational experiments on public benchmark instances demonstrate the success of the proposed collaborative approach, which outperforms the Differential Evolution and the Harmony search stand-alone.