Routing Agvs in Container Terminals by Using Q-learning
نویسندگان
چکیده
This paper suggests a routing method for automated guided vehicles (AGVs) in port terminals by using a Q-learning technique. One of the important issues for the efficient operation of automated guided vehicle system (AGVS) is to find the shortest time route instead of the shortest distance route which is usually being used in practice. For the estimation of the travel time, the waiting time must be estimated accurately. This study proposes a method for estimating the waiting time of vehicles resulting from the interference among vehicles during the travel by using the Q-learning technique. An experiment was performed to evaluate the performance of the learning algorithm by a simulation technique. The performance of the learning-based routes was compared to that of the shortest distance routes by the simulation study.
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