Distributed-elite local search based on a genetic algorithm for bi-objective job-shop scheduling under time-of-use tariffs

The rapid growth of electricity demand has led governments around the world to implement energy-conscious policies, such as time-of-use tariffs. The manufacturing sector can embrace these policies by implementing an innovative scheduling system to reduce its energy consumption. Therefore, this study...

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Veröffentlicht in:	Evolutionary intelligence Jg. 14; H. 4; S. 1581 - 1595
Hauptverfasser:	Kurniawan, Bobby, Song, Wen, Weng, Wei, Fujimura, Shigeru
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021 Springer Nature B.V
Schlagworte:	Applications of Mathematics Artificial Intelligence Bioinformatics Control Electric power demand Energy consumption Energy costs Engineering Genetic algorithms Job shop scheduling Job shops Manufacturing Mathematical and Computational Engineering Mechatronics Perturbation Research Paper Robotics Searching Statistical Physics and Dynamical Systems Tariffs Time of use electricity pricing Electricity cost Time-of-use tariffs Bi-objective job shop scheduling Genetic algorithm Total weighted tardiness
ISSN:	1864-5909, 1864-5917
Online-Zugang:	Volltext
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