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Not AvailableThis article deals with the problem of obtaining efficient designs for 2-color microarray experiments where same set of genes are spotted on each array. In the literature, optimality aspects of designs for microarray experiments have been investigated under a restricted model invloving array and variety effects. The dye effects have been ignored from the model. If dye effects are also included in the model, then the structure of the design becomes that of a row-column design where arrays represent columns, dyes represent rows and varieties represent treatments. Further, the array effects in microarray experiments may be taken as random (see e.g. Kerr and Churchill (2001a), Lee(2004)). For obtaining efficient row-column designs under fixed/mixed effects model, exchange and interchange algorithms of Eccleston and Jones(1980) and Rathore et al. (2006) have been modified. The algorithm has been translated into a computer program using Microsoft Visual C++. The algorithm is general in nature and can be used for generating efficient row-column designs for any 2 <= k < v, where v is the number of treatments (varieties) and k is number of rows(dyes). Here, the algorithm has been exploited for computer aided search of efficient row-column designs for making all possible pairwaise treatment comparisons for k = 2 (2-color microarray experiments) in the parametric range 3 <= v <= 10, v <= b <= v(v-1)/2; 11<=v <= 25, b = v and (v, b) = (11,13), (12,14), (13,14) and (13,15), where b is the number of arrays (columns). Efficient row-column designs obtained with higher efficiencies than the best available designs and even designs. The robustness aspect of efficient row-column designs obtained under fixed effects model and best available designs were investigated under a mixed effects model. Strength of the algorithm for obtaining row-column designs for 3-color microarray experiments has been demonstrated with the help of examples.Not Availabl