Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Topology optimization of compliant mechanism using multi-objective particle swarm optimization
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Empirical comparison of MOPSO methods: guide selection and diversity preservation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Rapid prototyping using evolutionary approaches: part 2
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Evolutionary multi-objective optimization and decision making for selective laser sintering
Proceedings of the 12th annual conference on Genetic and evolutionary computation
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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.