Please use this identifier to cite or link to this item:
Kia, Hamidreza
Ghodsypour, Seyed Hassan
Davoudpour, Hamid
Year of Publication: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 13 [Year:] 2017 [Issue:] 3 [Pages:] 297-306
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.
Dynamic flexible flow line
Genetic programming
Persistent Identifier of the first edition: 
Creative Commons License:
Document Type: 

Files in This Item:

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.