Integer and constraint programming models for the straight and U-shaped assembly line balancing with hierarchical worker assignment problem


Işık E. E., Yıldız Ş. A.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, sa.1, ss.1-24, 2023 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1080/00207543.2023.2290699
  • Dergi Adı: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1-24
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The solution to the assembly line balancing with the hierarchical worker assignment problem (ALB-HWP) provides the optimal allocation of workers and tasks to the stations that minimise the totalworker cost. In the ALBHWP, tasks differ in terms of the qualification requirements of workers, andthe qualification levels of workers are hierarchical. In the hierarchical workforce structure, a lowerqualified worker can be replaced by higher qualified ones with higher costs, while the vice versa isnot applicable. This problem has only been studied for straight assembly lines so far. In this paper,we introduce the ALBHWP for U-shaped assembly lines. We developed integer and constraint pro-gramming models for solving the ALBHWP and compared their effectiveness using an extensive setof benchmark instances. We solved the ALBHWP for straight and U-shaped assembly lines compar-atively. Constraint programming models have been statistically proven to provide better qualitysolutions faster than integer programming models. Besides, the CP model outperforms the onlyavailable metaheuristic in the literature for the S-ALBHWP in almost all problem sizes. Another obser-vation is that a U-shaped line design is more cost-effective than a straight line design, but solving theALBHWP for U-shaped lines is more difficult regarding computational complexity.