Influencing parameters of evolutionary algorithms for sequencing problems

Several problems in computer aided design (CAD) of integrated circuits (ICs) have to solve sequencing problems. For this reason many algorithms for solving these problems have been proposed. Especially, evolutionary algorithms (EAs) have been successfully applied in the past in these areas. We study the influence of different parameters on run time and quality for one specific problem of large practical importance for CAD of ICs, i.e. finding the optimal variable ordering of ordered binary decision diagrams (OBDDs). We consider different genetic operators and a problem specific heuristic. Our study shows that the influence of problem specific knowledge is much more significant than fine tuning the EA, especially if runtime is also considered as an optimization criterion. Our results directly transfer to other sequencing problems.