  One of the significant breakthroughs in quantum computation is Grover's
algorithm for unsorted database search. Recently, the applications of Grover's
algorithm to solve global optimization problems have been demonstrated, where
unknown optimum solutions are found by iteratively improving the threshold
value for the selective phase shift operator in Grover rotation. In this paper,
a hybrid approach that combines continuous-time quantum walks with Grover
search is proposed so that the search is accelerated with improved threshold
values. By taking advantage of the quantum tunneling effect, better threshold
values can be found at the early stage of the search process so that the
sharpness of probability improves. The results between the new algorithm,
existing Grover search, and classical heuristic algorithms are compared.
