This study presents an optimal set of process parameter values for air jet loom machine in weaving process using Taguchi designed experiment, response surface method and genetic algorithm together so as to minimize the rate of yarn breakage. The Taguchi designed experiment is used to develop the combination of selected parameters for speed, pressure, warp tension, backrest height and relative humidity. Each parameter possesses five levels and constructed by Minitab18. Signal to noise ratio, optimal parameter combination and ANOVA are determined. All selected parameters were found to be significant that the corresponding yarn breakage rate reduced from 87 to 32 per shit. The response surface method is used to build different regression models that represent yarn breakage rate and possible optimal regions, in line with parameter interaction, are examined from the plot effect. It reduced the yarn breakage less than 32 per shift. Moreover, a genetic algorithm was employed to propose the lowest possible yarn breakage rate using Matlab2014a, for which the best fit regression model has been taken as an objective function from response surface method or regression analysis and some functional algorithms were developed to generate possible offspring (new solutions) that yield the best parameter combination. From genetic algorithm optimization, the global minimum value was found to be 0.5 near to 1 yarn breakage per hour. Therefore, it can be decided that this optimization technique could result in the combination of process parameters that reduce the yarn breakage rate from 87 to 8 per shift. Finally, it is concluded that implementing the results of Taguchi designed experiment improved the production of fabric by 0.72m per hour and the proposed genetic algorithm optimization can improve production of fabric by 1.01m per hour. This implies that the employment of response surface method and genetic algorithm can provide better solution than Taguchi designed experiment. The findings are of great significance to the textile weaving industry to improve production since the yarn breakage frequency and the subsequent machine downtime would decrease. Furthermore, the results can be extended to similar industries and the overall positive effect is an important contribution for the country’s economy.