A genetic algorithm for generating optimal assembly plans

In this paper, we propose a genetic algorithm that generates and assesses assembly plans. An appropriately modified version of the well-known partially matched crossover, and purposely defined mutation operators allow the algorithm to produce near-optimal assembly plans starting from a randomly initialised population of (possibly non-feasible) assembly sequences. The quality of a feasible assembly sequence is evaluated based on the following three optimisation criteria: (i) minimising the orientation changes of the product; (ii) minimising the gripper replacements; and (iii) grouping technologically similar assembly operations. Two examples that endorse the soundness of our approach are also included.