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@PhDThesis{Chaves:2009:MeHÝBu,
               author = "Chaves, Antonio Augusto",
                title = "Uma meta-heur{\'{\i}}stica h{\'{\i}}brida com busca por 
                         agrupamentos aplicada a problemas de otimiza{\c{c}}{\~a}o 
                         combinat{\'o}ria",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2009",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2009-03-10",
             keywords = "Otimiza{\c{c}}{\~a}o combinat{\'o}ria, 
                         meta-heur{\'{\i}}sticas, busca por agrupamentos, 
                         localiza{\c{c}}{\~a}o de facilidades, caixeiro viajante, linha 
                         de produ{\c{c}}{\~a}o, combinatorial optimization, 
                         metaheuristics, clustering search, location of facilities, 
                         traveling salesman, assembly line.",
             abstract = "Esta tese apresenta um m{\'e}todo h{\'{\i}}brido, denominado 
                         Busca por Agrupamentos (CS, do ingl{\^e}s Clustering Search), que 
                         consiste em detectar dinamicamente regi{\~o}es promissoras no 
                         espa{\c{c}}o de busca baseando-se na frequ{\^e}ncia em que 
                         s{\~a}o amostradas nestas regi{\~o}es as solu{\c{c}}{\~o}es 
                         geradas por uma meta-heur{\'{\i}}stica. Um processo de 
                         agrupamento iterativo {\'e} executado em conjunto com a 
                         meta-heur{\'{\i}}stica, agrupando as solu{\c{c}}{\~o}es 
                         similares e mantendo solu{\c{c}}{\~o}es que sejam 
                         representativas para os grupos de solu{\c{c}}{\~o}es. As 
                         regi{\~o}es promissoras devem ser exploradas t{\~a}o logo sejam 
                         descobertas, por meio de heur{\'{\i}}sticas de busca local 
                         espec{\'{\i}}ficas para o problema abordado. S{\~a}o propostas 
                         algumas aplica{\c{c}}{\~o}es do CS a diferentes problemas de 
                         Otimiza{\c{c}}{\~a}o Combinat{\'o}ria encontrados na 
                         literatura, tais como, Problema de \$ p\$ -Medianas Capacitado, 
                         Problema de Agrupamento Centrado Capacitado, Problema do Caixeiro 
                         Viajante com Coleta de Pr{\^e}mios e o Problema de Balanceamento 
                         e Designa{\c{c}}{\~a}o de Trabalhadores em Linhas de 
                         Produ{\c{c}}{\~a}o. Esses problemas possuem diferentes 
                         caracter{\'{\i}}sticas e particularidades, sendo assim, {\'e} 
                         poss{\'{\i}}vel analisar o comportamento do CS em diversas 
                         situa{\c{c}}{\~o}es. Nessas abordagens s{\~a}o utilizadas 
                         diferentes meta-heur{\'{\i}}sticas para gerar 
                         solu{\c{c}}{\~o}es para o processo de agrupamento do CS, e 
                         tamb{\'e}m um m{\'e}todo gerador de solu{\c{c}}{\~o}es 
                         aleat{\'o}rias. Os testes computacionais mostram o potencial do 
                         CS para resolu{\c{c}}{\~a}o desses problemas de 
                         otimiza{\c{c}}{\~a}o, colocando-o como uma alternativa para 
                         problemas que necessitem ser resolvidos de forma aproximada e em 
                         um tempo computacional competitivo. Conclus{\~o}es a respeito dos 
                         componentes e par{\^a}metros do CS tamb{\'e}m s{\~a}o 
                         apresentadas. ABSTRACT: This thesis presents a hybrid method, 
                         denominated Clustering Search (CS), that consists of detecting 
                         dynamically promising regions in the search space based on the 
                         frequence that are sampled in these regions the solutions 
                         originated from the metaheuristic. A iterative clustering process 
                         is executed in ensembling the metaheuristic, grouping the similar 
                         solutions and keeping solutions that are representative to the 
                         clusters. The promising regions must be explored as soon as they 
                         are discovered, by means of local search heuristics. Some 
                         applications of CS are proposed in different combinatorial 
                         optimization problems found in literature like the Capacitated 
                         p-Median Problem, Capacitated Centred Clustering Problem, Prize 
                         Collecting Traveling Salesman Problem and the Assembly Line Worker 
                         Assignment and Balancing Problem. These problems have different 
                         characteristics and particularities, therefore, it is possible to 
                         analyse the behavior of CS in several situations. In these 
                         approaches different metaheuristics are utilized to generate 
                         solutions for the clustering process of CS, and also a generator 
                         method of random solutions. The computational tests present the 
                         potential of CS for resolving these optimization problems, putting 
                         it as an alternative for the problems that demand to be solved in 
                         an approximate form and in a competitive computational time. 
                         Conclusions regarding the components and parameters of CS are also 
                         presented.",
            committee = "Yanasse, Horacio Hideki (presidente) and Lorena, Luiz Antonio 
                         Nogueira (orientador) and Senne, Edson Luiz Franca and Carvalho, 
                         Solon Ven{\^a}ncio de and Armentano, Vinicius Amaral and Costa, 
                         Alysson Machado",
           copyholder = "SID/SCD",
         englishtitle = "A hybrid metaheuristic with clustering search applied to 
                         combinatorial optmization problems",
             language = "pt",
                pages = "197",
                  ibi = "8JMKD3MGP8W/34NDEC8",
                  url = "http://urlib.net/rep/8JMKD3MGP8W/34NDEC8",
        urlaccessdate = "17 nov. 2019"
}


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