Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/172564 
Erscheinungsjahr: 
2017
Quellenangabe: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 13 [Issue:] 3 [Publisher:] Springer [Place:] Heidelberg [Year:] 2017 [Pages:] 297-306
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.
Schlagwörter: 
Scheduling
Dynamic flexible flow line
Simulation
Heuristics
Genetic programming
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article

Datei(en):
Datei
Größe





Publikationen in EconStor sind urheberrechtlich geschützt.