Multi-objective optimal design strategy under type-II progressive censoring with random dependent removal model

In designing an optimal life-testing experiment under a censoring setup‎, ‎the removal vector scheme is usually chosen by optimizing a suitable criterion function‎. ‎The criterion functions are usually constructed based on cost or variance functions‎, ‎and sometimes a combination of both‎. ‎This paper considers a multiple optimization problem in the context of Type-II progressive censoring with random dependent removal lifetime experiment‎. ‎A simple simulation algorithm is presented for obtaining the optimal scheme in a multi-objective optimal problem under the Type-II progressive censoring with random dependent removal model‎. ‎Several simulation studies are conducted to evaluate and compare the performance of the proposed strategy‎. ‎Finally‎, ‎some concluding remarks and future works are provided.