Please use this identifier to cite or link to this item:
Title: Multi-objective performance improvements of general finite single-server queueing networks.
Authors: Cruz, Frederico Rodrigues Borges da
Keywords: Genetic algorithm
Simulated annealing
Issue Date: 2018
Citation: CRUZ, F. R. B. da. Multi-objective performance improvements of general finite single-server queueing networks. Journal of Heuristics, v. 24, p. 757-781, 2018. Disponível em: <>. Acesso em: 19 mar. 2019.
Abstract: Optimizing the performance of general finite single-server acyclic queueing networks is a challenging problem and has been the subject of many studies. The version of the optimization problem treated here considers the minimization of the buffer areas and the service rates simultaneously with the maximization of the throughput. These are conflicting objectives, and the most appropriate methodology appears to be a multi-objective methodology. In fact, algorithms have previously been proposed, and the aim here is to show that the use of a mixed methodology can occasionally improve solutions without a significant increase in the computational costs. This paper shows that improvements in throughput can be achieved through a solution of a type of stochastic knapsack problem, which consists of redistributing the buffer spaces between the lines while preserving the overall capacity using a simulated annealing algorithm; that is, one objective is improved (the throughput) without worsening the other (the overall allocated capacity). A set of computational experiments are presented to demonstrate the effectiveness of the proposed approach. Additionally, some of the insights presented here may help scientists and practitioners in finite single-server queueing network planning.
ISSN: 1572-9397
Appears in Collections:DEEST - Artigos publicados em periódicos

Files in This Item:
File Description SizeFormat 
  Restricted Access
1,46 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.