A scenario-based approach for a green aggregate production planning in a multi-site manufacturing system with workforce transferring


Choopani Asgarabad H., Jafari-Raddani M. H., Zokaee M., Toragay O., Rabbani M., AGHSAMI A.

Journal of Industrial and Production Engineering, cilt.42, sa.7, ss.840-857, 2025 (ESCI, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 42 Sayı: 7
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1080/21681015.2025.2548441
  • Dergi Adı: Journal of Industrial and Production Engineering
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.840-857
  • Anahtar Kelimeler: aggregate production planning, carbon emission, energy minimization, multi-objective optimization, waste management, Workforce transferring
  • Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet

Özet

This paper presents an Aggregate Production Planning (APP) model that minimizes workforce-related costs in multi-site manufacturing systems by introducing an inter-site workforce transferring policy. This novel approach reallocates workers between sites, reducing the need for hiring or layoffs. Additionally, the APP integrates environmental objectives, directly minimizing energy consumption, carbon emissions, and waste generation, forming a Green APP (GAPP). To address uncertainties in subcontractors’ costs, capacity, and overtime production, a scenario-based approach is adopted. The problem is formulated as a multi-objective scenario-based mixed-integer linear programming model and solved using a combination of the LP-metric method and fuzzy AHP. The model was validated through test problems and real-world implementation, achieving over 60% cost reduction in workforce changes. This study contributes to the APP literature by proposing inter-site workforce transfer policy, integrating environmental considerations, and addressing uncertainties in subcontractor performance.