Abstract
Multiobjective optimization using a Reduced Space Searching Algorithm (RSSA) is employed to optimally design titanium alloys suitable for prosthetic applications, i.e., with high strength, low elastic modulus, adequate biocompatibility, and low costs. The objectives in question are conflicting in nature, and thus multiobjective optimization is the ideal candidate for approaching this problem. The latter was formulated in such a way that it was necessary to develop three separate objective functions for strength, elastic modulus, and economic costs. The biocompatibility issue was introduced as a constraint in the optimization process. To develop the objective functions for yield strength and elastic modulus, a two-layered fuzzy inference system is used. To take into account economical factors, a weighted sum-based model of the elemental constituent is developed, including the costs of the alloying additions. The compositions of the alloy found from the Pareto solutions show that the above objectives can be fulfilled in the case of β Ti-alloys only.
Published Version
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