Sliced Latin hypercube designs, introduced by Qian (2012), are widely used for computer experiments with qualitative and quantitative factors, multiple experiments, cross-validation and stochastic optimization. In this paper, we propose a new class of sliced Latin hypercube design, called the...

Combined-optimal designs (Li and Lin, 2003) are obviously the best choices for the initial designs if we partition the experiment into two parts with equal size to obtain some information about the process, especially for the case not considering the blocking factor. In this paper, the...

Minimum aberration and clear criteria are two important rules for selecting optimal fractional factorial designs, in both unblocked and blocked cases. In this paper, we first show that under some given conditions, a blocked design DB=(D,B) having blocked minimum aberration is equivalent to D...

Supersaturated design is a form of fractional factorial design and has recently received much interest because of its potential in factor screening experiments. This paper mainly concerns the existing criteria for mixed-level designs, i.e. the [chi]2(D) criterion (for design D) proposed by...

Latin hypercube designs have found wide application. Such designs guarantee uniform samples for the marginal distribution of each input variable. We propose a method for constructing orthogonal Latin hypercube designs in which all the linear terms are orthogonal not only to each other, but also...