Evolutionary multi-objective optimization and decision making for selective laser sintering

This paper proposes an integrated approach to arrive at optimal build orientations, simultaneously minimizing surface roughness ‘Ra’ and build time ‘T’, for object manufacturing in SLS process. The optimization task is carried out by two popularly known multi-objective evolutionary optimizers - NSGA-II (non-dominated sorting genetic algorithm) and MOPSO (multi-objective particle swarm optimizer). The performance comparison of these two optimizers along with an approximation of Pareto-optimal front is done using two statistically significant performance measures. Three proposals addressing the task of decision making, i.e. selecting one solution in presence of multiple tradeoff solutions, are introduced to facilitate the designer. The overall procedure is integrated into MORPE - Multi-objective Rapid Prototyping Engine. Several sample objects are considered for experimentation to demonstrate the working of MORPE. A careful study of optimal build directions for several compone...

• Type: Conference
• Year: 2010
• Where: GECCO
• Authors: Nikhil Padhye, Kalyanmoy Deb
• Keywords: GECCO 2010, Genetic Algorithms, Optimal Build, Optimization, Particle Swarm