Tabu Search Hybridized with Multiple Neighborhood Structures for the Frequency Assignment Problem

摘要

This study proposes a tabu search hybridized with 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 the number of frequencies used. Several novel and existing techniques are used to improve the efficiency of this algorithm. This includes a novel technique that aims to determine a lower bound on the number of frequencies required from each domain for a feasible solution to exist, 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. Our tabu search algorithm was tested on real and randomly generated benchmark datasets of the static problem and achieved competitive results.