Abstract
Abstract
This paper aims to develop a probabilistic approach for robust design with orthogonal experimental methodology in case of target the best on basis of the probabilistic multi-objective optimization. In the treatment, the difference of the target value and the arithmetic mean value of performance indicators of the alternatives is taken one objective to be minimum, and the square root of mean squared error of actual value of performance indicators from the target value of the alternatives is taken as the second objective to be minimum, which contribute their partial preferable probabilities to the alternative individually. As an application example, the probabilistic method for multi-objective optimization is combined with orthogonal experimental methodology to conduct the optimum design, range analysis is used to total preferable probability subsequently, and ranking sequence of total preferable probability of alternatives is used to complete the optimization option.