A Comparison of Evolutionary Approaches to the Shortest Common Supersequence Problem
C. Cotta
Computational Intelligence and Bioinspired Systems, J. Cabestany, A. Prieto, F. Sandoval (eds.),
Lecture Notes in Computer Science 3512, pp. 50-58, Springer-Verlag Berlin,
2005
The Shortest Common Supersequence problem is a hard combinatorial
optimization problem with numerous practical applications. Several
evolutionary approaches are proposed for this problem, considering
the utilization of penalty functions, GRASP-based decoders, or
repairing mechanisms. An empirical comparison is conducted, using
an extensive benchmark comprising problem instances of different
size and structure. The empirical results indicate that there is
no single best approach, and that the size of the alphabet, and
the structure of strings are crucial factors for determining
performance. Nevertheless, the repair-based EA seems to provide
the best performance tradeoff.