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. Contrary to earlier algorithms which only move vehicles to known customers, this paper investigates waiting and relocation strategies in which vehicles may wait at their current location or relocate to arbitrary sites. Experimental results show that waiting and relocation strategies may dramatically improve customer service, especially for problems that are highly dynamic and contain many late requests. The decisions to wait and to relocate do not exploit any problem-specific features but rather are obtained by including choices in the online algorithm that are necessarily sub-optimal in an offline setting.
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