Multi-objective enhanced memetic algorithm for green job shop scheduling with uncertain times
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2022Derechos
© 2021 The Author(s).
Publicado en
Swarm and Evolutionary Computation, 2022, 68, 101016
Publisher
Elsevier
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Palabras clave
Job shop scheduling
Fuzzy durations
Multi-objective
Makespan
Non-processing energy
Memetic algorithm
Abstract:
The quest for sustainability has arrived to the manufacturing world, with the emergence of a research field known as green scheduling. Traditional performance objectives now co-exist with energy-saving ones. In this work, we tackle a job shop scheduling problem with the double goal of minimising energy consumption during machine idle time and minimising the project’s makespan. We also consider uncertainty in processing times, modelled with fuzzy numbers. We present a multi-objective optimisation model of the problem and we propose a new enhanced memetic algorithm that combines a multiobjective evolutionary algorithm with three procedures that exploit the problem-specific available knowledge. Experimental results validate the proposed method with respect to hypervolume,
-indicator and empirical attaintment functions.
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