Dynamic Multiple Neighborhood Structures for the Static Frequency Assignment Problem

Abstract

This study proposes a dynamic multiple neighborhood structures to solve a variant of the frequency assignment problem known as the minimum order frequency assignment problem. This problem involves assigning frequencies to a set of requests while minimizing interference and the number of used frequencies. Several novel and existing techniques are used to improve the efficiency of this algorithm and make it different from other applications of multiple neighborhood structures in the literature. This includes solving the static problem by modeling it as a dynamic problem through dividing this static problem into smaller sub-problems, which are then solved in turn in a dynamic process using multiple neighborhood structures. Moreover, applying technique that aims to determine a lower bound on the number of frequencies required from each domain for a feasible solution to exist for each sub-problem, based on the underlying graph coloring model. These lower bounds ensure that the search focuses on parts of the solution space that are likely to contain feasible solutions. This study considers real and randomly generated benchmark datasets of the static problem and our approach achieved competitive results.