Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloQuantum-Inspired Evolutionary Multiobjective Optimization for a Dynamic Production Scheduling Approach
Anno di pubblicazione2018
Formato-
Autore/iFiasche, Maurizio; Liberati, Diego E.; Gualandi, Stefano; Taisch, Marco
Affiliazioni autoriPolitecn Milan; Natl Res Council Italy; Antoptima SA
Autori CNR e affiliazioni
  • DIEGO LIBERATI
Lingua/e
  • inglese
AbstractThe Production Scheduling is an important phase in a manufacturing system, where the aim is to improve the productivity of one or more factories. Finding an optimal solution to scheduling problems means to approach complex combinatorial optimization problems, and not all of them are solvable in a mathematical way, in fact a lot of them are part of the class of NP-hard combinatorial problems. In this paper a joint mixed approach based on a joint use of Evolutionary Algorithms and their quantum version is proposed. The context is ideally located inside two factories, partners and use cases of the white'R FP7 FOF MNP Project, with high manual activity for the production of optoelectronics products, switching with the use of the new robotic (re)configurable island, the white'R, to highly automated production. This is the first paper approaching the problem of the dynamic production scheduling for these types of production systems proposing a cooperative solving method. Results show this mixed method provide better answers and is faster in convergence than others.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da191
Pagine a201
Pagine totali11
RivistaSmart innovation, systems and technologies (Print)
Attiva dal 2010
Editore: Heidelberg - Heidelberg ;
Paese di pubblicazione: Germania
Lingua: inglese
ISSN: 2190-3018
Titolo chiave: Smart innovation, systems and technologies (Print)
Titolo proprio: Smart innovation, systems and technologies. (Print)
Titolo abbreviato: Smart innov. syst. technol. (Print)
Titolo alternativo: Smart innovation, systems and technology (Print)
Numero volume della rivista69
Fascicolo della rivista-
DOI10.1007/978-3-319-56904-8_19
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000439910800020)
Parole chiaveEvolutionary algorithms, PSO, QEA, QiEA, QPSO, Quantum EA, Scheduling
Link (URL, URI)-
Titolo parallelo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IEIIT — Istituto di elettronica e di ingegneria dell'informazione e delle telecomunicazioni
Moduli/Attività/Sottoprogetti CNR
  • DIT.AD007.007.004 : ICSB - Information and Control for Systems Biology
Progetti Europei-
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