Motion planning and scheduling with stochastic demands

Abstract

This paper considers the combinatorial problem of motion planning and scheduling with stochastic demands. Here, an autonomous vehicle with limited capacity is requested to serve workstations in an industrial environment. Its workstation has a stochastic demand which is revealed upon the arrival of the vehicle. This combined problem is solved by optimizing the vehicle’s schedule and route (minimum travel distance) under collision-free and vehicle-capacity constraints. An optimization strategy based on the combination of a genetic and micro-genetic algorithm is developed in order to determine the optimum solution. Experimental results demonstrate the effectiveness of the proposed approach.