Contributions to Conferences

Vehicle Routing and Break Scheduling by a Distributed Decision Making Approach

Abstract

We present a distributed decision making approach for the problem of combined vehicle routing and break scheduling. This problem consists of finding vehicle routes to service a set of customers such that a cost criterion is minimized and legal rules on driving and working hours are observed. In the literature, this problem is mostly analyzed from a central planning perspective. In practice, however, this problem is usually solved coactively by planners and drivers. One possible distribution of tasks is such that the planner does the clustering and routing of the customer requests and instructs the drivers which customers they have to visit in which order. Subsequently, the drivers decide upon their break schedules. We apply a framework for distributed decision making to model this planning scenario and propose various ways for planners to anticipate the process of tour fulfillment performed by the drivers. We analyze whether the way of anticipation has direct impact on the quality and usefulness of the plans representing the planner’s instructions for the drivers. Computational experiments performed on the planning situation of a single driver demonstrate that a high degree of anticipation by the planner has a positive impact on the overall planning process.