Multiobjective optimisation of robot location in a workcell using genetic algorithms

The paper deals with the automatic planning of robotic cell layout using multiobjective optimisation technique. The genetic algorithm developed allows one to reduce computing efforts by "growing" the required Pareto-optimal set from a small number of initial Pareto-optimal solutions that are located at the nodes of a rough grid. Various simulation results have demonstrated the efficiency of the proposed approach for different objective functions.