Engineering optimization has been developed for the economic design of
engineering systems, The conventional optimum is determined without c
onsidering noise factors. Thus, applications to practical problems may
be limited. Within current design practice, noises tend to be allowed
for by specification of closer tolerances, or the use of safety facto
rs. However, these approaches may be economically infeasible. Thus, th
e inclusion of design-variable noises is required for practical design
in optimization. A method is developed to find robust solutions for u
nconstrained optimization problems. The method is applied to problems
with discrete variables. The orthogonal array based on the Taguchi con
cept is utilized to arrange the discrete variables. Through several ex
amples, it is verified that the solutions from the suggested method ar
e more insensitive to noise than the conventional optimum within the r
ange of variations for design variables.