Multiproduct inventory and pricing problems are traditionally approached by estimating a presumed sufficiently accurate demand model and then optimizing with this specified model to determine optimal inventory and pricing decisions. However, obtaining an accurate demand model is nearly impossible because of unobservabl...
This paper proposes a biobjective formulation that balances prediction accuracy and cost minimization, termed decision-driven regularization, which is shown to be numerically superior to other benchmarks, such as ordinary least squares, random forest, XGBoost, SPO+, perturbation gradient, and learning and rank, in the...
G. Loke, Qin-Shen Tang, Yangge Xiao et al.· INFORMS journal on computing· 1 citation
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