Improving EAs for Sequencing Problems

Sequencing problems have to be solved very often in VLSI CAD. To obtain results of high quality, Evolutionary Algorithms (EAs) have been successfully applied in many cases. However, they often suffer from the high CPU time which is necessary for the computation. In this paper we propose three techniques to speed up EAs without loss of quality. We give a case study for the problem of optimizing the variable ordering of Binary Decision Diagrams (BDDs). Experimental results are given to demonstrate the efficiency of the approach. 1 Introduction Sequencing problems in general have to be solved in many applications. They have in common that an order of (integer) numbers has to be optimized with respect to some application-dependent measure, as e.g. the length of the traveling salesman's way in the Traveling Salesman Problem (TSP). Many algorithms have been proposed so far to solve this kind of problem. To obtain results of high quality, Evolutionary Algorithms (EAs) have been ..