This article presents a cuckoo search algorithm, via Lévy flight, considering the effects of coevolution on the displacement dynamics of animal communities, and applies this algorithm to the development of maximally distributed physical arrangements. Some variables are introduced such as egg weight and the acquired learning of host birds. The results show that the proposed algorithm prevails, in the majority of the interviewed instances, in the degree of distribution in comparison with the classic TARGET and ALVO methods, and with the Genetic Algorithm. The proposed algorithm was shown to be able to obtain a low degree of distribution in a satisfactory computational time, especially in large problems.
Recently, new types of layouts have been proposed in the literature in order to handle a large number of products. Among these are the fractal layout, aiming at minimization of routing distances. There are already researchers focusing on the design; however, we have noticed that the current approach usually executes several times the allocations of fractal cells on the shop floor up to find the best allocations, which may present a significant disadvantage when applied to a large number of fractal cells owing to combinatorial features. This paper aims to propose a criterion, based on similarity among fractal cells, developed and implemented in a Tabu search heuristics, in order to allocate it on the shop floor in a feasible computational time. Once our proposed procedure is modeled, operations of each workpiece are separated in n subsets and submitted to simulation. The results (traveling distance and makespan) are compared to distributed layout and to functional layout. The results show, in general, a trade-off behavior, that is, when the total routing distance decreases, the makespan increases. Based on our proposed method, depending on the value of segregated fractal cell similarity, it is possible to reduce both performance parameters. Finally, we conclude the proposed procedure shows to be quite promising because allocations of fractal cells demand reduced central processing unit time.
RESUMOEm 2019, quando a Organização Mundial da Saúde (OMS) decretou pandemia provocada pelo novo coronavírus, o sars COV-2, muitos gestores públicos experienciaram provações árduas em suas cidades, a qual reprima concomitantemente desperdício de vidas, tal como de empregos. Com o intuito de ensejar-lhes suporte, esse trabalho visa propôr um modelo conciso que atente as variáveis compreendidas como o número de mortos, letalidade do vírus, número de leitos, empregos e impostos arrecadados entre outras, que se associam e concebem respostas relevantes de modo a oferecer uma consistente resposta para deliberação. Os resultados denunciam que para os dados iniciais considerados, o lockdown (LD) de 0% tem mais êxito na economia e na arrecadação de impostos, sucedendo com efeitos mais reprimidos ao número de mortes.Palavras-chave: Modelagem, simulação, impacto na economia, impacto na saúde, poder de compra, pandemia e lockdown.
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