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CNF simplifiers play a very important role in minimising structured problem hardness. Although they can be used in an in-search process, most of them serve in a pre-search phase and rely on one form or another of resolution. Based on our understanding about problem structure, in the paper, we extend the single pre-search process to a multiple one in order to further simplify the hard structure in a problem. This extension boosts the performance of state-of-the-art clause learning and lookahead based SAT solvers when solving both satisfiable and unsatisfiable instances of many real-world hard combinatorial problems.