A GA is an optimization method which gets its motivation from natural evolution and the principle of the survival of the fittest, which makes species improve their chromosomal coding in order to better fit their environment. In a genetic algorithm, a chromosomal representation needs to be defined to represent one solution to the packing problem. Simulated environment applies selective pressure biased to better individuals in a population of solutions. A crossover operator mixes genetic materials from two individuals in some random, yet systematic way to create offspring, which should be improved from their parents. Parents are selected randomly from a population of individuals biased towards the above-average, which is most likely to improve the solution.
Selective laser sintering uses fine, heat-fusible powder to build a part.
The powder is melted by a CO 2 laser beam which follows the shape of the cross section of the part being built. Due to this supporting powder, parts can be arranged in any orientation and location inside the cylinder. After the laser has sintered the current layer, the building platform is lowered one layer thickness inside the cylinder and a new layer of powder is spread on the top of the previous one by a leveling roller. The selective laser sintering machine has very few restrictions in the part shapes which it can produce. Most prototyped parts are used in industry and are therefore complex in shape, having irregular surfaces, cavities, and holes.