Today's highly competitive businesses place a great emphasis on responsiveness to customers. Alternative methods in their early steps of development are ubiquitous across different industrial application domains to simultaneously optimize various quality characteristics of the process or product. These approaches aim to identify the setting of the process or product parameter to maximize the degree of overall satisfaction via robustness desirability function with respect to all the response types. They also allow the decision makers to assign distinct weights adjustment and to find trade-off settings between robustness and optimization and take their relative magnitudes into account. Properties of the variable neighborhood modified simplex search are demonstrated via the process parameter design of a cryogenic QS Freezer process. It is shown that it depicts the outperformance results in comparison with the existing operating condition. All data presented in this paper have been normalized to disguise actual performance results as the natural data are considered to be confidential. © 2013 American Scientific Publishers. All rights reserved.