Simulation-Based AGV Management with a Linear Dispatching Rule

This paper considers the problem of real-time dispatching of a fleet of heterogeneous automated guided vehicles (AGVs) with battery constraints. The AGV fleet is heterogeneous in terms of material handling capabilities; some can tow loads, some can lift loads while others manipulate loads with the assistance of a robotic arm. Transport requests arrive in real-time and include a soft time window, with late delivery incurring tardiness costs. Transport requests need to be assigned to a capable AGV based on required material handling capabilities with the objective to minimize a weighted sum of tardiness costs of transport requests and travel costs of AGVs. In this paper, an AGV-specific linear dispatching rule (LDR) learning approach is proposed to assign AGVs to randomly arriving transport requests in real time over a finite horizon. The proposed approach is compared with a heuristic policy from practice by using real-world data provided by our industry partner.