A Mixed Integer Linear Programming Model for the Distribution of Transport Tasks Among Heterogeneous Robots in a Factory

The growing need for automation of factories and their processes determines a constant increase in the use of robots to carry out various tasks. Multiple robots can do different tasks simultaneously, speeding up processes. This practice raises the question of how many robots are needed to service the entire process, given all the limitations of the operation. One of these limitations is due to the navigation systems used by the several robots in the environment. Line-followers robots, for example, can only meet some tasks but are cheaper than free-movement ones. In this work, we develop an optimization model for task allocation among the available robots to minimize execution delays using mixed integer linear programming, considering their navigation systems. With the model, it is possible to obtain the best task allocation for each robot and the order to perform such tasks, thus avoiding delays as much as possible and getting zero delays for the presented case, that emulates the process of a vehicle assembler factory line.