Integrated Multi-Objective Optimization Model for Supply Chain-CMS Alignment: A Cellular Manufacturing Perspective

Abstract

In response to increasing demand variability and the need for agile production, this study proposes an integrated multi-objective optimization model that aligns Cellular Manufacturing Systems (CMS) with Supply Chain Management (SCM) objectives. The model addresses key challenges such as supplier coordination, inventory efficiency, machine capacity management, and customer responsiveness. It simultaneously minimizes supply lead times and inventory holding costs, maximizes system flexibility, and reduces backorders. Operational parameters—including processing times, dynamic demands, machine-cell configurations, flexibility scores, and supplier lead times—are incorporated into a comprehensive decision-making framework. A constraint-aware Genetic Algorithm (GA) is developed to explore feasible part-to-machine-cell assignments while satisfying operational constraints. The model is validated through a case study with 13 parts, 6 machines, and 3 manufacturing cells over multiple periods. Results demonstrate significant improvements in system responsiveness, resource utilization, and flexibility, underscoring the model's practical value for manufacturers seeking leaner, more adaptive supply chain operations.