Motivated by the real-world problem of a logistics company, this paper proposes a novel distribution-free prescriptive analytics approach – termed kernelized ERM – to solve a complex two-stage capacity planning problem with multivariate demand and vector-valued capacity decisions and...

Motivated by the work with a leading maintenance service provider in the aviationindustry, this paper examines novel data-driven approaches to solving a certaintype of capacity-sizing problem—the multi-shift staffing problem—with uncertain,time varying arrival rates and patient "customers"...

Motivated by the overwhelming success of gradient boosting approaches in machine learning and driven by the need for explainable prescriptive analytics approaches in operations management (OM), we propose an explainable prescriptive analytics approach to solving complex OM problems: subgradient...