Maximum completion time under a learning effect in the permutation flowshop scheduling problem

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Küçük Resim

Tarih

2018

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