Multi-machine energy-aware scheduling

  • David Van Den Dooren
  • Thomas Sys
  • Túlio A. M. Toffolo
  • Tony Wauters
  • Greet Vanden Berghe
Research Paper
  • 135 Downloads

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.

Keywords

Scheduling Multi-machine Energy optimisation Heuristics 

Mathematics Subject Classification

90–08 Computational methods 90B35 Scheduling theory, deterministic 90C11 Mixed integer programming 90C59 Approximation methods and heuristics 68T20 Problem solving (heuristics, search strategies, etc.) 

Notes

Acknowledgments

Work supported by iMinds, IWT and the Belgian Science Policy Office (BELSPO) in the Interuniversity Attraction Pole COMEX. Editorial consultation provided by Luke Connolly (KU Leuven).

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Copyright information

© EURO - The Association of European Operational Research Societies 2016

Authors and Affiliations

  • David Van Den Dooren
    • 1
  • Thomas Sys
    • 1
  • Túlio A. M. Toffolo
    • 1
    • 2
  • Tony Wauters
    • 1
  • Greet Vanden Berghe
    • 1
  1. 1.Department of Computer Science, CODeS and iMinds-ITECKU LeuvenGhentBelgium
  2. 2.Department of ComputingFederal University of Ouro PretoOuro PretoBrazil

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