Solving multiple instances at once: the role of search and adaptation

Abstract

Having in mind the idea that the computational effort and knowledge gained while solving a problem’s instance should be used to solve other ones, we present a new strategy that allows to take advantage of both aspects. The strategy is based on a set of operators and a basic learning process that is fed up with the information obtained while solving several instances. The output of the learning process is an adjustment of the operators. The instances can be managed sequentially or simultaneously by the strategy, thus varying the information available for the learning process. The method has been tested on different SAT instance classes and the results confirm that (a) the usefulness of the learning process and (b) that embedding problem specific algorithms into our strategy, instances can be solved faster than applying these algorithms instance by instance.