The Reactive Tabu Search

We propose an algorithm for combinatorial optimization where an explicit check for the repetition of configurations is added to the basic scheme of Tabu search. In our Tabu scheme the appropriate size of the list is learned in an automated way by reacting to the occurrence of cycles. In addition, if the search appears to be repeating an excessive number of solutions excessively often, then the search is diversified by making a number of random moves proportional to a moving average of the cycle length. The reactive scheme is compared to a ”strict” Tabu scheme, that forbids the repetition of configurations and to schemes with a fixed or randomly varying list size. From the implementation point of view we show that the Hashing or Digital Tree techniques can be used in order to search for repetitions in a time that is approximately constant. We present the results obtained for a series of computational tests on a benchmark function, on the 0-1 Knapsack Problem, and on the Quadratic Assignment Problem.