Optimising the energy consumption is one of the most important issues in scheduling nowadays. In this work we consider a multi-objective optimisation for the well-known job-shop scheduling problem. In particular, we minimise the makespan and the energy consumption at the same time. We consider a realistic energy model where each machine can be in Off, Stand-by, Idle or Working state. We design an effective constraint-programming approach to optimise both the energy consumption and the makespan of the solutions. Experimental results illustrate the potential of the proposed method, outperforming the results of the current state of the art in this problem.

Energy-Aware Multiple State Machine Scheduling for Multiobjective Optimization

Oddi Angelo;Rasconi Riccardo;
2018

Abstract

Optimising the energy consumption is one of the most important issues in scheduling nowadays. In this work we consider a multi-objective optimisation for the well-known job-shop scheduling problem. In particular, we minimise the makespan and the energy consumption at the same time. We consider a realistic energy model where each machine can be in Off, Stand-by, Idle or Working state. We design an effective constraint-programming approach to optimise both the energy consumption and the makespan of the solutions. Experimental results illustrate the potential of the proposed method, outperforming the results of the current state of the art in this problem.
2018
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Inglese
Ghidini, Chiara; Magnini, Bernardo; Passerini, Andrea; Traverso, Paolo
AI*IA 2018 - Advances in Artificial Intelligence. AI*IA 2018
XVIIth International Conference of the Italian Association for Artificial Intelligence
11298
474
486
13
978-3-030-03839-7
https://link.springer.com/chapter/10.1007%2F978-3-030-03840-3_35
Springer
Berlin
GERMANIA
Sì, ma tipo non specificato
November 20-23, 2018
Trento, Italy
Constraint-programming
Job-shop scheduling
Energy considerations
Multi-objective optimisation
2
none
Oddi, Angelo; Rasconi, Riccardo; Gonzalez, Miguel A.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/399786
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