Variable Neighborhood Search in Hamming Space

Variable Neighbourhood Search (VNS) is one of the most used meta-heuristics for global optimization. We focus our attention on combinatorial problems and propose a new implementation of VNS in Hamming space. Together with the basic VNS approach initially proposed by Hansen and Mladenović, we present a comparison among the most known VNS variants and we adapt them for the Hamming space. Our VNS is coded in Java programming language and implements the interfaces of the binMeta public project, where other meta-heuristics were previously included. Our computational experiments, on a small selection of combinatorial problems, show that our new VNS implementations outperform the other meta-heuristics present in binMeta.