Multi-objective automated guided vehicle scheduling based on MapReduce framework

During material handling processes, automated guided vehicles (AGVs) pose a path conflict problem. To solve this problem, we proposed multi-objective scheduling model based on total driving distance and waiting time, used the A* planning algorithm to search shortest of AGV. By using speed control strategy, were able detect overlap time. Additionally, adopted an efficient MapReduce framework improve strategy execution efficiency. At last, system smart electrical connectors workshop was discussed verify combined with is feasible effective reduce AGV probability. The could be applied in replace manual production