New dispatching rules and due date assignment models for dynamic job shop scheduling problems

Teymourifar A., Ozturk G.

International Journal of Manufacturing Research, cilt.13, sa.4, ss.302-329, 2018 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13 Sayı: 4
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1504/ijmr.2018.095358
  • Dergi Adı: International Journal of Manufacturing Research
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.302-329
  • Anahtar Kelimeler: Dispatching rules, Due date assignment models, Dynamic job shop scheduling, Neural networks, Regression, Simulation
  • Anadolu Üniversitesi Adresli: Evet

Özet

Copyright © 2018 Inderscience Enterprises Ltd.In this paper, new due date assignment models and dispatching rules have been designed for the dynamic job shop scheduling problem. All of them have competitive results compared to the models from previous studies. The proposed dispatching rules have been evolved based on the modified and composite features of jobs. They have been compared with successful methods from the literature in a simulated environment. The simulation model has been validated by comparing the results with an analytical method. One of the rules has the best results in comparison with the other dispatching rules from the literature cited in this study. Another important matter which is considered in this paper is that the due date assignment model must be compatible with the used dispatching rule. Based on this approach, new due date assignment models are developed, which have the best results when combined with some dispatching rules.