Assembly line balancing problem with resource and sequence-dependent setup times (ALBPRS)


Kılınçcı Ö.

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, sa.1, ss.557-570, 2023 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2023
  • Doi Numarası: 10.17341/gazimmfd.757276
  • Dergi Adı: JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Art Source, Compendex, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.557-570
  • Anahtar Kelimeler: Assembly line balancing problem, assembly line balancing with resource and sequence dependent setup times, mathematical model, genetic algorithm, GENETIC ALGORITHM, SCHEDULING TASKS, MODEL
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The classical simple assembly line balancing problem (SALBP) has been extended with many real-life applications recently. One of these extensions is assembly line balancing with sequence-dependent setup times (ALBPS). In this study, ALBPS is extended with more than one resource at each workstation. Task is performed any resource at each workstation. More than one resource at each workstation can decrease the number of setups. Thus, the required number of the workstations on the line can reduce. The problem is called assembly line balancing with resource and sequence-dependent setup times (ALBPRS). ALBPRS is to assign the task to the workstations, to assign the tasks to the resource, and to sequence the tasks performed by the same resource at each workstation simultaneously. A mathematical model and a genetic algorithm are developed to solve the problem. The benchmark data set is generated for ALBPRS and the mathematical model and genetic algorithm are tested on the generated benchmark dataset. Results show that the proposed methods are efficient and using more than one resource at each workstation decreases the total number of the workstations in many test problems.