Highlights ► Problem: uncertain task durations in a vehicle routing problem with time windows. ► We propose preprocessing schemes ensuring task feasibility with a targeted risk level. ► Method for tuning the risk level for a globally optimal economic gain. ► Extensive testing on real-life data: such preprocessing is relevant in practice.
Abstract 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.
Handling uncertainties in vehicle routing problems through data preprocessing
Transportation Research Part E: Logistics and Transportation Review ; 48 , 3 ; 667-683
2011-10-29
17 pages
Article (Journal)
Electronic Resource
English
Handling uncertainties in vehicle routing problems through data preprocessing
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