Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/10422
Title: Multi-machine energy-aware scheduling.
Authors: Dooren, David Van Den
Sys, Thomas
Toffolo, Túlio Ângelo Machado
Wauters, Tony
Keywords: Energy optimisation
Heuristics
Issue Date: 2017
Citation: DOOREN, D. V. D. et al. Multi-machine energy-aware scheduling. EURO Journal on Computational Optimization, v. 5, n. 1-2, p. 285–307, mar. 2017. Disponível em: <https://link.springer.com/article/10.1007/s13675-016-0072-0>. Acesso em: 16 jun. 2018.
Abstract: The traditional set of manufacturing scheduling problems concern general and easy-to-measure economic objectives such as makespan and tardiness. The variable nature of energy costs over the course of the day remains mostly ignored by most previous research. This variability should not be considered an added complexity, but rather an opportunity for businesses to minimise their energy bill. More effectively scheduling jobs across multiple machines may result in reduced costs despite fixed consumption levels. To this end, this paper proposes a scheduling approach capable of optimising this largely undefined and, consequently, currently unaddressed situation. The proposed multi-machine energy optimisation approach consists of constructive heuristics responsible for generating an initial solution and a late acceptance hill climbing algorithm responsible for improving this initial solution. The combined approach was applied to the scheduling instances of the ICON challenge on Forecasting and Scheduling [The challenge is organized as part of the EU FET-Open: Inductive Constraint Programming (ICON) project (O’Sullivan et al., ICON challenge on forecasting and scheduling. UCC, University College Cork, ICON, Cork. http://iconchallenge.insight-centre.org/challenge-energy, 2014)] whereupon it was proven superior to all other competing algorithms. This achievement highlights the potential of the proposed algorithm insofar as solving the multi-machine energy-aware optimisation problem (MEOP). The new benchmarks are available for further research.
URI: http://www.repositorio.ufop.br/handle/123456789/10422
metadata.dc.identifier.uri2: https://link.springer.com/article/10.1007/s13675-016-0072-0
ISSN: 21924414
Appears in Collections:DECOM - Artigos publicados em periódicos

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