Multi-objective Optimisation and Multi-criteria Decision Making for FDM Using Evolutionary Approaches [chapter]

Nikhil Padhye, Kalyanmoy Deb
2011 Multi-objective Evolutionary Optimisation for Product Design and Manufacturing  
In this paper, we describe a systematic multi-objective problem solving approach, simulataneosly minimizing two conflicting goals -average surface roughness 'Ra' and build time 'T ', for object manufacturing in FDM process by usage of evolutionary algorithms. Popularly used multi-objective genetic algorithm NSGA-II and recently proposed multi-objective particle swarm optimization (MOPSO) algorithms, are employed for the optimization purposes. Statistically significant performance measures are
more » ... ployed to compare the two algorithms and means to arrive at approximate Pareto-optimal fronts are also suggested. To refine the solutions obtained by the optimizers, a mutation driven hill climbing local search is also proposed. Several suggestions and three new proposals pertaining to the issue of decision making in presence of trade-off solutions are also made. The overall procedure is integrated into a MORPE -Multi-objective Rapid Prototyping Engine. Several sample objects are considered for simulation to demonstrate the working of MORPE. Finally, a careful study of optimal build directions for several components considered indicates a trend, providing an insight into the FDM processes and can be considered useful for various practical RP applications.
doi:10.1007/978-0-85729-652-8_7 fatcat:7sqm5czqcrcjjeb7npowonb23m