Multi-criteria-based optimal life-testing plans under hybrid censoring scheme

In designing an optimal life-testing experiment under censoring setup, the design parameters are usually chosen by optimizing a suitable criterion function. The criterion function is chosen by using either a variance-based or a cost-based model, and sometimes a combination of both these factors. However, it is an optimization problem with a single objective function. In this article, a multi-criteria-based optimization problem is considered in the context of hybrid censored life-testing experiment. Both the variance and the cost factors are optimized simultaneously. The exact distribution of the maximum likelihood estimate of the lifetime model parameter is used to construct the optimality criteria. All the proposed methods are illustrated through numerical examples. One dataset is finally analyzed for real-life applications.