Augmented Weighted Tchebycheff-Based Approach for Sustainable Multi-Objective Workforce and Process Planning in Reconfigurable Manufacturing Environment

Alireza Ostovari (1) , Lyes Benyoucef (1) , Hichem Haddou Benderbal , Xavier Delorme (2, 3, 4, 5)

1 AMU - Aix Marseille Université
2 Mines Saint-Étienne MSE - École des Mines de Saint-Étienne
3 LIMOS - Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes
4 FAYOL-ENSMSE - Institut Henri Fayol
5 FAYOL-ENSMSE - Département Génie mathématique et industriel

This research examines the integration of workforce and process planning in reconfigurable manufacturing environment, focusing on sustainability's economic, social, and environmental dimensions. It evaluates social sustainability through new indicators, including flexible working hours and workforce hazard risks. A new mixed-integer linear programming model is proposed to minimize costs, social sustainability metric, production time, and hazardous waste. The model's effectiveness is assessed with RMS benchmarks using the augmented weighted Tchebycheff method for multi-objective optimization and data envelopment analysis to rank solutions, providing a detailed evaluation of RMS configurations.

Domaines: Modélisation et simulation

Alireza Ostovari, Lyes Benyoucef, Hichem Haddou Benderbal, Xavier Delorme. Augmented Weighted Tchebycheff-Based Approach for Sustainable Multi-Objective Workforce and Process Planning in Reconfigurable Manufacturing Environment. IFAC-PapersOnLine, 2024, 18th IFAC Symposium on Information Control Problems in Manufacturing (INCOM), Vienna, Austria, August 28-30, 2024, 58 (19), pp.109-114. ⟨10.1016/j.ifacol.2024.09.104⟩. ⟨emse-04709598⟩