Understanding the role of insertion and correction in the evolution of Golomb rulers

Abstract

An evolutionary algorithm designed to successfully search for Optimal Golomb rulers is presented. The proposed approach uses a binary representation to codify the marks contained in a ruler. Standard genetic operators are used. During evaluation, insertion and correction procedures are applied in order to improve the algorithm performance. Experimental results show that this approach is effective and capable of identifying good solutions. Furthermore, a comprehensive study is performed to understand the role of insertion and correction. Results reveal that the first method is essential to the success of the search process, whereas the importance of the second one remains unclear.