Abstract
This study considers the dynamic frequency assignment problem, where new requests gradually become known and frequencies need to be assigned to those requests effectively and promptly with the minimum number of reassignments. The problem can be viewed as a combination of three underlying problems: the initial problem, the online problem, and the repair problem. In this study, a heuristic approach is proposed to solve this problem using different solution methods for each underlying problem. Moreover, the efficiency of this approach is improved by means of the Gap technique, which aims to identify a good frequency to be assigned to a given request. For the purpose of this study, new dynamic datasets are generated from static benchmark datasets. It was found that the performance of our approach is better than the state-of-the-art approach in the literature across the same set of instances.