Exploiting the Crow Search Algorithm to Overcome the Bandpass Problem

In telecommunication networks, fiber optics is used to transfer data from a source to a destination. One of the common problems in the transmission process is called the Bandpass Problem (BP). BP concentrates on establishing a model that can transfer information on various wavelengths at a minimum cost using wavelength division multiplexing technology. The data is organized in packets involving various columns. The minimum cost can be obtained by finding the best row permutation in terms of cost in an acceptable time. Sundry studies have been exploited to find the minimum cost at an appropriate time. Although previous studies have reduced the cost and decreased the execution time, they have not reached optimality. Therefore, in this article, a mining technique using a metaheuristic method called the Crow Search Algorithm (CSA) was applied to achieve the aforementioned goal. The proposed method can find the global minimum cost by keeping the positions of the best row permutation in an acceptable time. The row permutation remains unchanged unless a new better row permutation is computed. The findings exhibited a great deal of insights into how the CSA method outperformed the genetic algorithm, simulated annealing, and the ant bee colony in most cases.