Rapid prototyping using evolutionary approaches

Abstract

In this paper we describe a multi-objective problem solving approach, simultaneously minimizing average surface roughness Ra and build Time T, for object manufacturing by Rapid Prototyping (RP) processes using evolutionary algorithms. Development of a package- Multi-objective Rapid Prototyping using evolutionary algorithms has been discussed. Popularly used multi-objective genetic algorithm NSGA-II and recently proposed Multi-objective particle Swarm Optimization (MOPSO), with SQP (Sequential Quadratic Programming) based intermittent local search, are employed for optimization purposes. The performances of these evolutionary optimizers are compared on sample objects and proposed procedure is validated based on results obtained.