Multi-objective optimal design strategy under type-II progressive censoring with random dependent removal model
نویسندگان
1 School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran
2 School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran
3 Faculty of Mathematics, Statistics and Computer Science, University of Sistan and Baluchestan
doi
10.22034/jsmta.2023.19974.1095چکیده
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.
