The nonstandard algorithm for constructing efficient conjoint experimental designs

Conjoint analysis is a research technique for measuring consumer preferences, and it is a method for simulating consumers' possible reactions to changes in current products or newly introduced products into an existing competitive market. One of the most critical steps in Conjoint analysis application is experimental designs construction. The purpose of an experimental design is to give a rough overall idea as to the shape of the experimental response surface, while only requiring a relatively small number of runs. These designs are expected to be orthogonal and balanced in an ideal case. In practice, though, it is hard to construct optimal designs and thus constructing of near optimal and efficient designs is carried out. There are several ways to quantify the relative efficiency of experimental designs. The choice of measure will determine which types of experimental designs are favored as well as the algorithms for choosing efficient designs. In this paper it is proposed the algorithm which combines one standard and one non-standard optimality criteria. The computational experiments were made, and results of comparison with algorithm implemented in commercial package SPSS confirm the efficiency of the proposed algorithm.