Closed-Loop Supply Chain Cost Optimization for Make-to-Order Production: A Case Study of A Shaft Manufacturing Enterprise
DOI:
https://doi.org/10.23055/ijietap.2026.33.2.11483Abstract
Make-to-order (MTO) systems require flexible production schedules and inventory management. The outcome of this study is a hybrid MTO Closed Loop Supply Chain (CLSC) model that combines raw/recycled materials for cost minimization. In this study, a mixed-integer programming (MIP) model and implement two solution approaches have been developed: a simplified mixed-integer linear programming (MILP) for computational efficiency and a genetic algorithm to solve full mixed-integer nonlinear programming MINLP. Monte Carlo simulation was used to account for variability in demand, return rates, and production processes. The contributions of this work include: CLSC model tailored to MTO with dual MIP formulations with comparative analysis of MILP and MINLP performance, practical insights into implementing cost-efficient hybrid CLSC. There is a research gap, which most studies assume deterministic conditions in MTO CLSC. The presented work covers this gap and models the complexity of MTO where demand, lead times, and return rates are uncertain. The model in this work is developed based on shaft manufacturing industrial setups. However, the proposed methodology can be applied in other contexts with needed customization and changes to accommodate the specifications of other context which are characterized by high-value component recovery.
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