Optimization of Supplier Selection and Order Allocation Considering Supply Risk based on MRFO Algorithm

Ting Wu; Gengjun Gao

doi:10.6981/FEM.202505_6(5).0014

Authors

Ting Wu
Gengjun Gao

DOI:

https://doi.org/10.6981/FEM.202505_6(5).0014

Keywords:

Supplier Selection and Order Allocation; Uncertain Environment; Supply Risk; Manta Ray Foraging Optimization.

Abstract

This study develops a multi-period procurement model integrating Mean-CVaR optimization to address supply-demand uncertainty in automotive supply chains. We propose a modified Manta Ray Foraging Optimization algorithm that minimizes total costs while controlling quality and delivery risks under stochastic conditions. Using real manufacturing data, the model demonstrates 39.6% cost reduction versus conventional methods while maintaining 95% service levels. Key findings identify optimal risk parameters (λ=0.4) and prove multi-supplier strategies (≥3 partners) enhance resilience when α≥0.9. The framework provides actionable insights for sustainable procurement planning.

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