Skip to Main Content
The shortest common superstring (SCS) problem, known to be NP-complete, seeks the shortest string that contains all strings from a given set. In this paper, we present a novel coevolutionary algorithm-the Puzzle Algorithm-where a population of building blocks coevolves alongside a population of solutions. We show experimentally that our novel algorithm outperforms a standard genetic algorithm (GA) and a benchmark greedy algorithm on instances of the SCS problem inspired by deoxyribonucleic acid (DNA) sequencing. We next compare our previously presented cooperative coevolutionary algorithm with the Co-Puzzle Algorithm-the puzzle algorithm coupled with cooperative coevolution-showing that the latter proves to be top gun. Finally, we discuss the benefits of using our puzzle approach in the general field of evolutionary algorithms.