Hybrid Quantum Computing -- Tabu Search Algorithm for Partitioning Problems: preliminary study on the Traveling Salesman Problem

Quantum Computing is considered as the next frontier in computing, and it is\nattracting a lot of attention from the current scientific community. This kind\nof computation provides to researchers with a revolutionary paradigm for\naddressing complex optimization problems, offering a significant speed\nadvantage and an efficient search ability. Anyway, Quantum Computing is still\nin an incipient stage of development. For this reason, present architectures\nshow certain limitations, which have motivated the carrying out of this paper.\nIn this paper, we introduce a novel solving scheme coined as hybrid Quantum\nComputing - Tabu Search Algorithm. Main pillars of operation of the proposed\nmethod are a greater control over the access to quantum resources, and a\nconsiderable reduction of non-profitable accesses. To assess the quality of our\nmethod, we have used 7 different Traveling Salesman Problem instances as\nbenchmarking set. The obtained outcomes support the preliminary conclusion that\nour algorithm is an approach which offers promising results for solving\npartitioning problems while it drastically reduces the access to quantum\ncomputing resources. We also contribute to the field of Transfer Optimization\nby developing an evolutionary multiform multitasking algorithm as\ninitialization method.\n