A comparison of the performance of artificial intelligence techniques for optimizing the number of kanbans

Alabas C., Altiparmak F., Dengiz B.

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, cilt.53, sa.8, ss.907-914, 2002 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 53 Sayı: 8
  • Basım Tarihi: 2002
  • Doi Numarası: 10.1057/palgrave.jors.2601395
  • Dergi Adı: JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.907-914
  • Anahtar Kelimeler: kanban, Just in Time system, kanban-controlled system, simulation optimization, genetic algorithms, simulated annealing, tabu search, neural network, TABU SEARCH, OPTIMUM NUMBER, NEURAL-NETWORK, SIMULATION, OPTIMIZATION, DESIGN, METAMODEL, SYSTEM
  • Gazi Üniversitesi Adresli: Evet

Özet

This paper discusses the use of modem heuristic techniques coupled with a simulation model of a Just in Time system to find the optimum number of kanbans while minimizing cost. Three simulation search heuristic procedures based on Genetic Algorithms, Simulated Annealing, and Tabu Search are developed and compared both with respect to the best results achieved by each algorithm in a limited time span and their speed of convergence to the results. In addition, a Neural Network metamodel is developed and compared with the heuristic procedures according to the best results. The results indicate that Tabu Search performs better than the other heuristics and Neural Network metamodel in terms of computational effort.