A mathematical model and artificial bee colony algorithm for the lexicographic bottleneck mixed-model assembly line balancing problem

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Kucukkoc I., Buyukozkan K., Satoğlu Ş. I., Zhang D. Z.

JOURNAL OF INTELLIGENT MANUFACTURING, cilt.30, sa.8, ss.2913-2925, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 30 Sayı: 8
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1007/s10845-015-1150-5
  • Dergi Adı: JOURNAL OF INTELLIGENT MANUFACTURING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2913-2925
  • Anahtar Kelimeler: Lexicographic bottleneck, Assembly line balancing, Mixed-model lines, Mathematical model, Artificial bee colony algorithm, DEPENDENT SETUP TIMES, GENETIC ALGORITHM, PARALLEL WORKSTATIONS, U-LINES, OPTIMIZATION, DESIGN, FORMULATION
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Typically, the total number of required workstations are minimised for a given cycle time (this problem is referred to as type-1), or cycle time is minimised for a given number of workstations (this problem is referred to as type-2) in traditional balancing of assembly lines. However, variation in workload distributions of workstations is an important indicator of the quality of the obtained line balance. This needs to be taken into account to improve the reliability of an assembly line against unforeseeable circumstances, such as breakdowns or other failures. For this aim, a new problem, called lexicographic bottleneck mixed-model assembly line balancing problem (LB-MALBP), is presented and formalised. The lexicographic bottleneck objective, which was recently proposed for the simple single-model assembly line system in the literature, is considered for a mixed-model assembly line system. The mathematical model of the LB-MALBP is developed for the first time in the literature and coded in GAMS solver, and optimal solutions are presented for some small scale test problems available in the literature. As it is not possible to get optimal solutions for the large-scale instances, an artificial bee colony algorithm is also implemented for the solution of the LB-MALBP. The solution procedures of the algorithm are explored illustratively. The performance of the algorithm is also assessed using derived well-known test problems in this domain and promising results are observed in reasonable CPU times.