A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems
Küçük Resim Yok
Tarih
2009
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ATLANTIS PRESS
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this paper a new artificial immune system (AIS) algorithm is proposed to solve multi objective fuzzy flow shop scheduling problems. A new mutation operator is also described for this AIS. Fuzzy sets are used to model processing times and due dates. The objectives are to minimize the average tardiness and the number of tardy jobs. The developed new AIS algorithm is tested on real world data collected at an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed AIS is demonstrated by comparing it with genetic algorithms. Computational results demonstrate that the proposed AIS algorithm is more effective meta-heuristic for multi objective flow shop scheduling problems with fuzzy processing time and due date.
Açıklama
Anahtar Kelimeler
Fuzzy flow shop, new artificial immune system, multi objective, engine cylinder liner manufacturing process
Kaynak
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
WoS Q Değeri
Q4
Scopus Q Değeri
Cilt
2
Sayı
3
