Compound Optimal Design for Generalized Exponential Distribution under Progressively Censored Data

In this paper, we will discuss a compound optimal design for Generalized Exponential distribution under progressive censoring. In order to achieve the best results for a life-testing experiment with more than one objective, compound optimal designs are often employed to achieve the best outcomes for the investigation. For compound design, three examples are described by considering cost function with a trace, with variance and with determinant of inverse Fisher information. The best design is calculated through a graphical solution technique that is easy to understand and precise. We compare an exhaustive search method with a meta-heuristic approach to discover an optimal scheme for progressively censored data. One example demonstrates the advantage of using compound optimal designs against constraint optimal designs. Finally, real-world data collection is investigated in a life-testing experiment to demonstrate the usefulness of the compound optimal design.