Multi-objective optimization of energy-efficient production schedules using genetic algorithms
dc.contributor.author | Küster, Tobias | |
dc.contributor.author | Rayling, Philipp | |
dc.contributor.author | Wiersig, Robin | |
dc.contributor.author | Pardo, Francisco Denis Pozo | |
dc.date.accessioned | 2022-10-04T09:45:11Z | |
dc.date.available | 2022-10-04T09:45:11Z | |
dc.date.issued | 2021-10-04 | |
dc.description.abstract | The optimization of production schedules to be more energy efficient while still meeting production goals is a difficult task: How to schedule and distribute production tasks to meet production goals, while making best use of fluctuating energy market prices and availability of locally installed energy sources? Although a large body of related work exists in this domain, most of those seem to focus on individual aspects and not the whole picture. In this paper, a genetic algorithm for optimization of production schedules with respect to energy consumption, peak shaving, and makespan is presented, that also takes into account that tasks can be performed in different ways, having different characteristics. The algorithm has been successfully employed within the SPEAR project by applying it for optimization of an automotive production line and for the pathway of an automated guided vehicle. | en |
dc.description.sponsorship | TU Berlin, Open-Access-Mittel – 2021 | en |
dc.description.sponsorship | BMBF, 01IS17024G, Verbundprojekt: SPEAR - Smart Prognosis of Energy with Allocation of Resources | en |
dc.description.sponsorship | BMBF, 01IS17024H, Verbundprojekt: SPEAR - Smart Prognosis of Energy with Allocation of Resources | en |
dc.identifier.eissn | 1573-2924 | |
dc.identifier.issn | 1389-4420 | |
dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/17023 | |
dc.identifier.uri | https://doi.org/10.14279/depositonce-15802 | |
dc.language.iso | en | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
dc.subject.ddc | 004 Datenverarbeitung; Informatik | de |
dc.subject.other | industrial optimization | en |
dc.subject.other | genetic algorithms | en |
dc.subject.other | energy modeling | en |
dc.subject.other | schedule optimization | en |
dc.title | Multi-objective optimization of energy-efficient production schedules using genetic algorithms | en |
dc.type | Article | en |
dc.type.version | publishedVersion | en |
dcterms.bibliographicCitation.doi | 10.1007/s11081-021-09691-3 | en |
dcterms.bibliographicCitation.journaltitle | Optimization and Engineering | en |
dcterms.bibliographicCitation.originalpublishername | Springer Nature | en |
dcterms.bibliographicCitation.originalpublisherplace | Heidelberg | en |
tub.accessrights.dnb | free | en |
tub.affiliation | Fak. 4 Elektrotechnik und Informatik::Inst. Wirtschaftsinformatik und Quantitative Methoden::FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT) | de |
tub.affiliation.faculty | Fak. 4 Elektrotechnik und Informatik | de |
tub.affiliation.group | FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT) | de |
tub.affiliation.institute | Inst. Wirtschaftsinformatik und Quantitative Methoden | de |
tub.publisher.universityorinstitution | Technische Universität Berlin | en |