A Queueing System to Jobs Scheduling Problem in AGVs

Automated Guided Vehicles are mobile robots de-signed for transportation purposes, and one of the most important problems associated with intelligent logistics is the problem of job scheduling. The goal is to find the optimal allocation of job execution by the number of available devices. The problem can be resolved with a simulation in which the different scenarios are evaluated. However, creating such a simulation model requires a statistical description of the problem. In this paper, we implement the simulation model for the AGV environment. Based on the mathematical description of the model, the discrete event simulation is created using the Python programming language and the SimPy library. We use the simulation to compare the solution of the job scheduling problem using the simulated annealing and genetic algorithms.