We present a human-guidable and general tabu search algorithm. Our work expands on previous interactive optimization techniques that provide for substantial human control over a simple, exhaustive search algorithm. User experiments in four domains confirm that human guidance can improve the performance of tabu search and that people obtain superior results by guiding a tabu algorithm than by guiding an exhaustive algorithm.