Complexity Estimation for Genetic Assembly Sequence Planning

Assembly planning involves in determining a particular assembly priority from which associated restraint factors such as geometric features, assembly time, tools, and machines are taken into account of arranging a feasible assembly sequence based upon the planner’s individual heuristics. Suchlike planning lately may implement genetic algorithms (GAs) to go towards the assembly sequence features of speed and flexibility. However, finding feasible solutions or even optimal solutions is arduous to identify the global optimal solution in a short period. The purpose of this paper essentially aims at establishing a complexity index for practitioners to decide what type of algorithm employed, namely traditional GAs, or ameliorative GAs like Guided-GAs. The threshold of the proposed complexity judgment is hinged on the square of preceding constraints and the quantity of nodes in the event. As the complexity increases the frequency of feasible solutions found did not exactly come up by traditional GAs. According to the proposed index assembly sequence problems are asserted more constraints comparatively while the complexity approaches to 70 or above.