The price of commitment in online stochastic vehicle routing

This paper considers online stochastic multiple vehicle routing with time windows in which requests arrive dynamically and the goal is to maximize the number of serviced customers. Early work has focused on very flexible routing settings where the decision to assign a vehicle to a customer is delayed until a vehicle is actually deployed to the customer. Motivated by real applications that require stability in the decision making, this paper considers a setting where the decision to assign a customer request to a vehicle must be taken when that request is accepted. Experimental results suggest that this constraint severely degrades the performance of existing algorithms. However, the paper shows how the use of stochastic information for vehicle assignment and request acceptance improves decision quality considerably. Moreover, the use of resource augmentation quantifies precisely the cost of commitment in online vehicle routing