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It is well known that evolutionary algorithms often perform much better when augmented with a local search mechanism. While many local search methods exist for combinatorial optimization problems, there are relatively few methods designed to work over continuous fitness landscapes. This paper describes a novel continuous space local search algorithm for evolutionary algorithms that emulates army ant swarm raids. Our preliminary results show the method is remarkably effective.