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.