New criteria of comparing multi-level supersaturated designs are proposed and their properties are studied. A new class of multi-level supersaturated designs are obtained by collapsing a U-type uniform design to an orthogonal array. A global optimization algorithm, the threshold accepting algorithm, is then applied to search for the best supersaturated designs under any prespecified criterion. Examples show that these newly constructed supersaturated designs have good modeling properties.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics