Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
A Hybrid Multi-objective Evolutionary Approach to Engineering Shape Design
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Innovization: innovating design principles through optimization
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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In structure topology optimization, the applied boundary and support conditions are often fixed in a-priori. These conditions can affect the behavior and the properties of single-piece elastic structures known as compliant mechanisms. In this paper, the same aspect is explored for path generating compliant mechanisms by considering them as design variables and their values are evolved using customized NSGA-II algorithm. Three examples are solved and the innovative facts among the applied boundary and support conditions are presented. The elastic structures are also presented in this paper.