Code and Data Repository for Refined Wasserstein Distributionally Robust Optimization for Contract Pricing: The Value of Optimality Conditions in Transactions

This paper considers a contract pricing problem in a two-tier supply chain with information asymmetry. To ensure decision reliability with small data, a Wasserstein-based data-driven distributionally robust pricing model using a dual-source data set is developed to maximize the seller’s worst-case profit. Numerical experiments demonstrate that proposed solution methods have higher computational efficiency compared to traditional methods, and derived optimal decisions exhibit superior out-of-sample performance compared to classical data-driven decisions. The codes in this repository can be used to replicate the results of the numerical experiments.