The increasing demand for customized products has significantly increased the complexity of supply
chain operations, making efficient path planning an important issue for reducing overall supply chain
costs. This study proposes a supply chain network (SCN)-based path optimization model for
customized product supply chains. The proposed model simultaneously optimizes node selection and
transportation routes while minimizing transportation, processing, and fixed operating costs. To solve
the optimization problem, a Genetic Algorithm (GA) with integer encoding is employed. Numerical
experiments are conducted under different supply chain network scales to evaluate the effectiveness
of the proposed model. The experimental results indicate that the proposed approach can effectively
identify cost-efficient node configurations and transportation routes while maintaining stable
convergence across different network scales. The proposed model provides an effective optimization
framework for customized product supply chain design and offers useful managerial implications for
supply chain network planning and cost management.
The increasing demand for customized products has significantly increased the complexity of supply
chain operations, making efficient path planning an important issue for reducing overall supply chain
costs. This study proposes a supply chain network (SCN)-based path optimization model for
customized product supply chains. The proposed model simultaneously optimizes node selection and
transportation routes while minimizing transportation, processing, and fixed operating costs. To solve
the optimization problem, a Genetic Algorithm (GA) with integer encoding is employed. Numerical
experiments are conducted under different supply chain network scales to evaluate the effectiveness
of the proposed model. The experimental results indicate that the proposed approach can effectively
identify cost-efficient node configurations and transportation routes while maintaining stable
convergence across different network scales. The proposed model provides an effective optimization
framework for customized product supply chain design and offers useful managerial implications for
supply chain network planning and cost management.