Production in a two-machine flowshop scheduling environment with uncertain processing and setup times to minimize makespan


Aydilek A., Aydilek H., Allahverdi A.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, sa.9, ss.2803-2819, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1080/00207543.2014.997403
  • Dergi Adı: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2803-2819
  • Anahtar Kelimeler: dominance relation, flowshop, makespan, scheduling, uncertain setup and processing time
  • Gazi Üniversitesi Adresli: Hayır

Özet

A wide range of uncertainties exists in some real-world production environments which result in uncertain setup and/or processing times. Factors such as crew skills, shortages in equipment and resource breakdowns can be the sources of these uncertainties. This study considers a two-machine production flowshop scheduling problem where both setup and processing times are treated as uncertain variables. The objective is to minimise makespan which is an effective way of resource utilisation. There exists a dominance relation in the literature for the two-machine flowshop scheduling problem with uncertain setup and processing times. However, the dominance relation has not been evaluated. In this study, we evaluate the existing dominance relation. Moreover, a new dominance relation is established and shown to be more effective than the existing one. Furthermore, twenty-five implementations of a polynomial time algorithm are developed. Extensive computational experiments are conducted to evaluate the performance of the implementations of the algorithm. The computational experiments indicate that the overall gap (error) of the best implementation of the algorithm is less than 0.3% when compared to the optimal solution. Moreover, the performance of this implementation of the algorithm is the best one when compared to the remaining implementations for all the considered experimental environments. Additionally, the performance of this implementation of the algorithm is shown to be insensitive to the uncertainty in setup times.