A VALUE-ADDED APPROACH FOR AUTOMATED GUIDED VEHICLE TASK ASSIGNMENT

Efficient material flow is essential in achieving high productivity le vels. Design and control of the material handling system directly affe ct the efficiency of the material flow. In the case of automated guide d vehicle (AGV) systems, this translates to guidepath design, AGV disp atching, scheduling, and routing. The focus of this paper is on vehicl e dispatching, or vehicle task assignment, which is defined as the sel ection of the next load for pickup and delivery. The algorithm develop ed in this research is inherently a demand-driven strategy (that is, p ull), which further prioritizes the loads requiring an AGV according t o the value added to them as they go through the manufacturing process es. Benchmarking for several performance factors, such as throughput a nd flow time, through simulation experiments shows this algorithm to o utperform some of the best dispatching rules reported in the literatur e.