Network infrastructure design with a multilevel algorithm

• Published in: Expert systems with applications Vol. 40; no. 9; pp. 3471 - 3480
• Main Authors: Silva, Hideson Alves da, de Souza Britto, Alceu, Oliveira, Luiz Eduardo Soares de, Koerich, Alessandro L.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01-07-2013; Elsevier
• Subjects: Algorithms; Applied sciences; Brazil; Communities; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Design engineering; Exact sciences and technology; Expert systems; Flows in networks. Combinatorial problems; Genetic algorithm; Multilevel; Multilevel optimization process; Network design; Networks; Operational research and scientific management; Operational research. Management science; Particle swarm optimization; Software; Multilevel optimization process; Network design; Genetic algorithm; Particle swarm optimization; Costs; Dependability; Process planning; Project management; Interconnected power system; Unfolding; Distributed system; Experimental result; Database; Swarm intelligence; Planning; Localization; Cost lowering; Firm
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2012.12.055

► We describe an algorithm to design low cost and optimized network infrastructures. ► The existing dependency among the different network levels is considered. ► We report a significant cost reduction in the network design. ► Different optimization techniques are evaluated with the proposed algorithm. ► A new database composed of real and georeferenced data is built and made available.
This paper presents a novel algorithm to deal with the network design problem, which optimizes the network levels considering their interdependency. The idea is to design a low cost and optimized network providing the number and the geographic location of devices as well as the links among them for each network level, while taking into account the existing dependency among them. In addition, a new database composed of real and georeferenced data is created and make available for the research community. This database contains three datasets that represent distinct projects related to geographic regions of the city of Curitiba (Brazil). The experimental results show that the proposed algorithm provides a significant cost reduction in the network design. The savings of this proposal go from 1% to 40% (depending on the network size, number of levels and demand nodes), making it attractive for companies that spend a considerable amount of resources in network projects and deployment.