Accelerated Life Testing (ALT) is an important technique to assess the reliability and lifetime of components with long life and high reliability. To some expensive products, it is difficult to supply a large of samples and long test time to carry out the life testing, so this paper studies accelerated model and its statistical method based on hybrid Weibull distribution under variable synthetic stresses. Based on the cumulative exposure model aforementioned, the parameters of accelerated model can be estimated with ALT data and its accelerated stress profile. However, the development of multi-stresses ALT under variable stress profile leads to a bottleneck problem on parameter estimation when evaluated parameters are greater than three. Direct toward the optimum difficulties with multi-parameters in Maximum Likelihood Estimation (MLE), this paper presents an Improved Float Genetic Algorithm (IFGA), which adopts the fuzzy algorithm in the float genetic algorithm to approach the global optimum solution. Application of hydraulic pump indicates that this method can reduce test time and test samples greatly.