Evolutionary multi-objective optimization and decision making for selective laser sintering
Abstract
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 trade-off 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 components indicates a trend, providing insight into the SLS processes which can be regarded highly useful for various practical RP applications.
Authors: Nikhil Padhye, Kalyanmoy Deb
Published in: Genetic and Evolutionary Computation Conference (GECCO) (2010)