“…Multiple objectives are considered sequentially in (Alici & Shirinzadeh, 2004;Krefft et al, 2005;Risoli et al, 1999;Stocco et al, 1998) by searching for parameter sets resulting in near optimal kinematic performance and then selecting the design exhibiting the best dynamic performance from this reduced parameter space. Task-priority (Chen et al, 1995), probabilistic weighting (McGhee et al, 1994), composite index (Lee et al, 2001), and tabular methods (Yoon & Ryu, 2001) are among the other scalarization approaches that consider multiple criteria. Scalarization methods possess the inherent disadvantage of their aggregate objective functions requiring preferences or weights to be determined apriori, i.e before the results of the optimization process are actually known (de Weck, 2004).…”