Variable returns to scale DEA—Taguchi approach for ternary additives optimization in expansive soil subgrade enhancement

Abstract In this study, variable returns to scale (VRS) data envelopment analysis was integrated into the Taguchi approach optimize ternary additives for expansive soil enhancement. The selected were sawdust ash (SDA), quarry dust (QD) and ordinary Portland cement (OPC). set as input variables while multiple responses obtained from experiments performed with orthogonal array output variables. Each row in defined a decision making unit (DMU) optimization process output-oriented VRS model used obtain efficiency score each DMU. Next, benevolent formulation utilized multipliers inputs outputs which subsequently determine cross scores cross-efficiency construct matrix. Thereafter, mean (MCES) determined Parameter level that maximizes MCES chosen optimal parameter. Optimum combination of found at A6 B2 C3. Lastly, confirmatory by blending optimum showed effectiveness method enhancement properties.