Maximum completion time under a learning effect in the permutation flowshop scheduling problem
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Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Univ Cincinnati Industrial Engineering
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The permutation flowshop scheduling problem under a position-based learning effect is addressed in this study. Minimization of the maximum completion time (make span) is considered for the identified problem. The mathematical programming model is established to find optimal solutions for small-sized problems. Furthermore, meta-heuristics are developed to achieve effective solutions for large-sized problems encountered in real applications. These meta-heuristics are the genetic algorithm which is a population-based solution approach, the kangaroo and the variable neighborhood search algorithms which both are single-solution-based solution approaches. In addition, different solution methods, which are in the literature for similar problem structures, are also used. Improved heuristics are evaluated according to optimal results for small-sized problems and according to performance differences between each other for large-sized problems.
Açıklama
Anahtar Kelimeler
learning effect, flowshop, make span, genetic algorithm, kangaroo algorithm, variable neighborhood search algorithm
Kaynak
International Journal Of Industrial Engineering-Theory Applications And Practice
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
25
Sayı
2
Künye
closedAccess
