New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Industrial Engineering International Springer Journals

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by The Author(s)
Subject
Engineering; Industrial and Production Engineering; Quality Control, Reliability, Safety and Risk; Facility Management; Engineering Economics, Organization, Logistics, Marketing; Appl.Mathematics/Computational Methods of Engineering
ISSN
1735-5702
eISSN
2251-712X
D.O.I.
10.1007/s40092-017-0185-y
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Journal of Industrial Engineering InternationalSpringer Journals

Published: Jan 19, 2017

References

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