Gene expression programming based meta-modelling approach to production line design

Baykasoglu A.

INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, cilt.21, sa.6, ss.657-665, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21 Sayı: 6
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1080/09511920701370753
  • Dergi Adı: INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.657-665
  • Anahtar Kelimeler: production line design, soft computing, gene expression programming, simulation, meta-modelling, ARTIFICIAL NEURAL-NETWORKS, MANUFACTURING SYSTEMS, SIMULATION, OPTIMIZATION, REGRESSION, MACHINES
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

Fierce competition in today's economy forces companies to fully optimize their processes in order to supply customers with high-quality products on time with lowest possible cost. Designing optimal production lines is a major step ahead in satisfying customer needs. Owing to the stochastic and highly nonlinear nature of the production lines, their optimal design is not easy and requires usage of advanced tools and techniques. In the present paper one of the new generation soft computing technique that is known as gene expression programming (GEP) is used to develop a meta-model from extensive simulation experiments for the multiple objective design of a production line. The developed meta-model is used to optimize production line design with multiple objective tabu search algorithm (MOTS). It is found out that GEP and MOTS can be effectively used to model and solve production line design problems.