Solving The Cut Width Optimization Problem With A Genetic Algorithm Approach

The Cut width Minimization Problem is a NP-Hard problem that is found in the VLSI design, graph drawing, design of compilers and linguistics. Developing solutions that could solve it efficiently is important due to its impact in areas that are critical for society. It consists in finding the linear array of an undirected graph that minimizes the maximum number of edges that are cut. In this paper we propose a genetic algorithm applied to the Cut width Minimization Problem. As the configuration of a metaheuristic has a great impact on the performance, we also propose a Fuzzy Logic controller that is used to adjust the parameters of the GA during execution time to guide it during the exploration process.