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Accelerated Life tests expose the products to greater environmental stress levels so that we can obtain lifetime and degradation measurements in a more timely techniques for performing an ALT include constant stress. In this paper presents methods for planning accelerated life tests for models in which the logarithm of time-to-failure follows a location-scale distribution and the location parameter is a function of stress. Different choices of test-stress levels and test length can result in different precision of the estimate of the reliability of the product at normal-use conditions. A test plan that gives minimum variance of the maximum likelihood estimates (MLEs) of the unknown location and scale parameters of the log-location-scale family of distributions at specified stress levels by suitably determining the test length. Under this model, the determination of the optimal choice of τ for lognormal distributions are addressed using the asymptotic variance optimality criterion. Numerical illustration is also provided.