Clustering search multi-heurística paralelo para resolução do problema de localização de contadores de tráfego em redes de transporte

• Ano de defesa: 2019
• Autor(a) principal: Monteiro, Renan Costalonga
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Informática; Centro Tecnológico; UFES; Programa de Pós-Graduação em Informática
• Palavras-chave em Português: Meta-heurísticas; Clustering Search; GRASP; ILS; Simulated annealing; Paralelismo; Metaheuristics; Parallelism; subject.br-rjbn; Ciência da Computação
• Link de acesso: http://repositorio.ufes.br/handle/10/13836

The Traffic Counting Location Problem (TCLP) aims to determine the amount of sensors selecting locations for installing them so that a transport network is fully covered. In general, vehicle counter sensors are used to collect information related to vehicles flow in the network. Due to the high cost of installation, we have to minimize the number of sensors used to cover all the network. In this work, two new approaches of the Clustering Search (CS) metaheuristic were developed using the GRASP and ILS metaheuristics as solution generators. In addition, an innovative and unexplored approach of CS using parallel search metaheuristics for solution generation is also proposed. The methods were tested using a set of instances that describes the road structure of each Brazilian state, and the results obtained were equal or better to the best ones presented in the literature for all instances.