Abstract
In this paper we present a novel strategy to implement the paradigm of tabu search within a hybrid quantum-classical scheme based on quantum annealing to solve otimization problems with a particular focus on QUBO problems. The proposed algorithm is based on an iterative structure where the representation of an objective function into the annealer architecture is modified and already visited solutions are penalized by a tabu search. We prove the convergence of the algorithm to a global optimum in the case of general QUBO problems. Our technique is an alternative to the direct reduction of a given optimization problem into the sparse annealer graph.
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URL
https://arxiv.org/abs/1810.09342