Heuristics for job shop scheduling with volatile machine constraints

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

An alteration of the job shop scheduling problem, concerning advertisement scheduling on digital advertisement spaces, is presented. Dispatching Rules (DR), Iterated Local Search (ILS) and Genetic Algorithms (GA) are discussed and applied to the problem space. The results show that ILS is the best performing heuristic, and surpasses the other heuristics especially in large problem spaces (≥ 100 machines, ≥ 100 jobs). The results match previously made findings, which indicates that effects on large-scale problems should be further researched in conjunction with amalgam algorithms between DR, GA and ILS.

OriginalspracheEnglisch
TitelProceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
Redakteure/-innenBing Xu
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten389-393
Seitenumfang5
ISBN (elektronisch)9781467396127
DOIs
PublikationsstatusVeröffentlicht - 28 Feb. 2017
Veranstaltung2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 - Xi'an, China
Dauer: 3 Okt. 20165 Okt. 2016

Publikationsreihe

NameProceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016

Konferenz

Konferenz2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
Land/GebietChina
OrtXi'an
Zeitraum03.10.201605.10.2016

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