基于多目标遗传算法的山药真空干燥工艺优化

为了得到山药切片真空干燥的最优工艺参数,以平均干燥速率Y₁、单位能耗Y₂、复水比Y₃和白度指数Y₄为试验指标,以干燥温度T、压强V和切片厚度L为影响因素进行进行Box-Behnken响应面优化试验,通过多元非线性回归分析建立各指标的数学模型,最后分别使用加权评分法和遗传算法进行多目标优化。结果表明:多目标遗传算法优化结果更合理,得到的山药切片真空干燥最优工艺参数为:干燥温度63.76℃、压强0.0532 MPa和切片厚度2.46 mm,所对应的指标值为:平均干燥速率0.00897 g/(g·min)、单位能耗14.205 kW·h/kg、复水比2.078和白度指数81.220。

Optimization of Vacuum Drying Technology of Yam Based on Multi-Objective Genetic Algorithm

In order to obtain the optimal process parameters of vacuum drying of yam slices, Box-Behnken response surface optimization test was carried out with average drying rate Y₁, unit energy consumption Y₂, rehydration ratio Y₃ and whiteness index Y₄ as the test indexes, and drying temperature T, pressure V and slice thickness L as the influencing factors. The mathematical model of each index was established by multiple nonlinear regression analysis. Finally, the weighted scoring method and genetic algorithm were used for multi-objective optimization. The results show that the optimization result of multi-objective genetic algorithm is more reasonable. The optimum vacuum drying parameters are as follows: drying temperature 63.76℃, pressure 0.0532 MPa and slice thickness 2.46 mm.The corresponding index values are average drying rate 0.00897 g/(g·min), unit energy consumption 14.205 kW·h/kg, rehydration ratio 2.078 and whiteness index 81.220.