In this paper we propose the use of the genetic algorithm (GA) as a tool to solve multi-objective optimization problems in flexure jointed hexapods. Using the concept of heuristic mutation, a modified GA-based multi-objective optimization technique is proposed and the passive parameters' optimization problems in a flexure jointed hexapod system are solved. The passive parameters found include the spring and the damping parameters in each strut of the hexapod. The results produced by this new approach are compared to those produced by other practical selection techniques, proving that this technique is more flexible. Thus, the genetic algorithm can be used as a reliable numerical optimization tool in such problems.
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