Optimizing driver consistency in the vehicle routing problem under uncertain environment

This paper investigates the construction of routes over multiple days while maintaining driverconsistency, which requires that the multi-day service of each customer be provided by as fewdifferent drivers as possible over a planning horizon. Furthermore, if one customer is assigned todifferent drivers over multiple days, it is desirable that services are provided by one driver on asmany days as possible. To optimize this driver consistency, a new quantitative measure of driverconsistency is defined. In the proposed vehicle routing problem with driver consistency, driverconsistency is modeled in the objective function. Another contribution is that we model thevehicle routing problem with driver consistency considering uncertainties in customer demands,travel times, and service times. Uncertain programming models for the considered problemare developed utilizing uncertainty theory. A hybrid algorithm with large neighborhood searchand simulated annealing is designed to address the proposed NP-hard problem. Computationalexperiments are conducted on several datasets to highlight the performance of the proposedapproach and the models. The impacts of uncertainty and the trade-off between the total traveltime and driver consistency are also analyzed to reveal some managerial insights.Our analysis shows that uncertainty has negative impacts on minimizing total travel timewhile can improve driver consistency in some cases; Remarkable reduction in the total traveltime can be achieved with little damage on driver consistency; However, totally focusing onminimizing total travel time comes at the price of sacrificing driver consistency drastically