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Constraint programming and local search are two well known optimization technologies. In recent years, methods for combining these two technologies have been put forward, one of which advocates the use of constraint programming for searching the local neighborhood of the current solution. We present a search technique which improves on the performance of this constraint programming-based local search method and perform experiments on a variety of both simple and more complex combinatorial problems. We also demonstrate the benefit of combining local and complete search methods.