Handling uncertainties in vehicle routing problems through data preprocessing

This paper presents a global preprocessing methodology for handling uncertainties in operations management. Beyond theoretical considerations on solution feasibility, the methodology provides practitioners with a Monte Carlo simulation‐based framework for effective risk management. The main strength of this methodology is being easily applicable to almost any decision problem. Application field of the paper is a real‐life workforce management problem for which we propose several mixed integer formulations as well as dedicated solution algorithms. Extensive numerical tests on real‐life instances assess the benefit from preprocessing schemes when performed as recommended by our approach, and thus prove its practical relevance.