Multi-objective evolutionary algorithm for solving energy-aware fuzzy job shop problems

A growing concern about the environmental impact of manufacturing processes and in particular the associated energy consumption has recently driven some researchers within the scheduling community to consider energy costs in addition to more traditional performance-related measures, such as satisfac...

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Veröffentlicht in:	Soft computing (Berlin, Germany) Jg. 24; H. 21; S. 16291 - 16302
Hauptverfasser:	González-Rodríguez, Inés, Puente, Jorge, Palacios, Juan José, Vela, Camino R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2020 Springer Nature B.V
Schlagworte:	Artificial Intelligence Computational Intelligence Control Energy consumption Energy costs Energy management Engineering Evolutionary algorithms Fuzzy sets Genetic algorithms Heuristic Job shop scheduling Job shops Mathematical Logic and Foundations Mechatronics Methodologies and Application Multiple objective analysis Robotics Scheduling Uncertainty Variables Job shop scheduling Energy efficiency Fuzzy durations Multi-objective Genetic algorithm Due dates
ISSN:	1432-7643, 1433-7479
Online-Zugang:	Volltext
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