A data structure for spanning tree optimization problems

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Barbosa, Marco Aurélio Lopes
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-29082019-141240/
Resumo: Spanning tree optimization problems are related to many practical applications. Several of these problems are NP-Hard, which limits the utility of exact methods and can require alternative approaches, like metaheuristics. A common issue for many metaheuristics is the data structure used to represent and manipulate the solutions. A data structure with efficient operations can expand the usefulness of a method by allowing larger instances to be solved in a reasonable amount of time. We propose the 2LETT data structure and uses it to represent spanning trees in two metaheuristics: mutation-based evolutionary algorithms and local search algorithms. The main operation of 2LETT is the exchange of one edge in the represented tree by another one, and it has O(√n) time, where n is the number of vertices in the tree. We conducent qualitative and quantitative evaluations for 2LETT and other structures in the literature. For the main operation of edge exchange in evolutionary algorithms, the computational experiments show that 2LETT has the best performance for trees with more than 10,000 vertices. For local search algorithms, 2LETT is the best option to deal with large trees with large diameters.