Data visibility, sourcing flexibility, and pricing decisions in supply chains

This article extends the supply chain planning problem under risk by including the visibility of purchasing information and sourcing flexibility. A novel geometric index is developed to measure purchasing visibility by including different attributes of the required data visibility level. The problem is formulated as a mixed integer non-linear optimisation model. We tailor an outer approximation (OA) algorithm as a decomposition-based algorithm to solve the resultant mathematical model. Our research experiments indicate how the basic OA algorithm could be applied in the non-convex models by utilising a reformulation-linearisation technique and a convexification scheme. Moreover, the superiority of our proposed OA algorithm is shown in terms of solution quality and CPU time.

Automated summary

This article extends the supply chain planning problem under risk by including the visibility of purchasing information and sourcing flexibility. A novel geometric index is developed to measure purchasing visibility by including different attributes of the required data visibility level. The problem is formulated as a mixed integer non-linear optimization model. We tailor an outer approximation algorithm as a decomposition-based algorithm to solve the resultant mathematical model. Our research experiments indicate the superiority of the proposed algorithm in terms of solution quality and CPU time.