Use este identificador para citar ou linkar para este item: https://repositorio.ufrn.br/handle/123456789/31052
Título: Enhanced arc-flow formulations to minimize weighted completion time on identical parallel machines
Autor(es): Kramer, Arthur Harry Frederico Ribeiro
Dell’Amico, Mauro
Iori, Manuel
Palavras-chave: Scheduling;Arc-flow formulations;Parallel machines;Weighted completion time
Data do documento: 16-Mai-2019
Editor: Elsevier
Referência: KRAMER, Arthur; DELL'AMICO, Mauro; IORI, Manuel. Enhanced arc-flow formulations to minimize weighted completion time on identical parallel machines. European Journal of Operational Research, v. 275, p. 67-79, 2019. Disponível em: https://www.sciencedirect.com/science/article/pii/S0377221718309809?via%3Dihub Acesso em 10 dez 2020. https://doi.org/10.1016/j.ejor.2018.11.039.
Resumo: We consider the problem of scheduling a set of jobs on a set of identical parallel machines, with the aim of minimizing the total weighted completion time. The problem has been solved in the literature with a number of mathematical formulations, some of which require the implementation of tailored branch-and-price methods. In our work, we solve the problem instead by means of new arc-flow formulations, by first representing it on a capacitated network and then invoking a mixed integer linear model with a pseudo-polynomial number of variables and constraints. According to our computational tests, existing formulations from the literature can solve to proven optimality benchmark instances with up to 100 jobs, whereas our most performing arc-flow formulation solves all instances with up to 400 jobs and provides very low gap for larger instances with up to 1000 jobs
URI: https://repositorio.ufrn.br/handle/123456789/31052
ISSN: 0377-2217
Aparece nas coleções:CT - DEP - Artigos publicados em periódicos

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