In this paper, we tackle the Cyclic Bandwidth Sum Problem, consisting in minimizing the sum of the bandwidth of the edges of an input graph computed in a cycle-structured host graph. This problem has been widely studied in the literature due to its multiple real-world applications, such as circuit design, migration of telecommunication networks, or graph drawing, among others. Particularly, we tackle this problem by proposing a multistart procedure whose main components are a new greedy constructive algorithm and an intensification strategy based on the Variable Neighborhood Search metaheuristic. The constructive procedure introduces two different greedy criteria to determine each step of the construction phase, which can be used for other related problems. Additionally, we illustrate how to perform an efficient exploration of the neighborhood structure by using an alternative neighborhood. Our algorithmic proposal is evaluated over a set of 40 instances previously studied in the literature and over a new proposed set of 66 well-known instances introduced in this paper. The obtained results have been satisfactory compared with the ones obtained by the best previous algorithm in the state of the art. The statistical tests performed indicate that the differences between the methods are significant.
Artificial Intelligence Phd Student
Sergio Cavero was born Madrid (Spain) on September 24, 1997. He graduated in Software Engineering from Universidad Politécnica de Madrid in 2019. During his undergraduate studies he made a stay at the University of Bradford (UK). In addition, he was awarded twice with the ‘Beca de Excelencia of the Comunidad de Madrid, and also awarded for the Best Final Degree Project. Later, he completed a Master’s Degree in Artificial Intelligence at the same university (UPM) obtaining awards for Best Academic Record (‘Premio José Cuena’) and Best Master’s Thesis. He academic results lend him be beneficiary of one of the ‘Ayudas Para la Formación de Profesorado Universitario (FPU)’, funded by the Spanish Government. He is currently carrying out his doctoral thesis at the Universidad Rey Juan Carlos, supervised by Professors Abraham Duarte and Eduardo G. Pardo. His main research interests focus on the interface among Computer Science, Artificial Intelligence and Operations Research. Most of his publications deal with the development of metaheuristics procedures for optimization problems modeled by graphs.
Abraham Duarte is Full Professor in the Computer Science Department at the Rey Juan Carlos University (Madrid, Spain). He has done extensive research in the interface between computer science, artificial intelligence, and operations research to develop solution methods based on Computational Intelligence (metaheuristics) for practical problems in operations-management areas such as logistics and supply chains, telecommunications, decision-making under uncertainty and optimization of simulated systems.