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

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

Ting Wu, Gengjun Gao

Frontiers in Economics and Management, (2025), Vol.6, No.5, pp.143-159

Published: May 14, 2025

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

PDF: Download Full Text PDF

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.

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

APA Citation: Ting Wu, Gengjun Gao (2025). Optimization of Supplier Selection and Order Allocation Considering Supply Risk based on MRFO Algorithm. Frontiers in Economics and Management, 6(5), 143-159. https://doi.org/10.6981/FEM.202505_6(5).0014

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