Multi-objective Optimal Test Planning Using Bayesian Reliability Estimation: A Case for Equipment Under Development

This paper proposes a multi-objective optimization framework for planning reliability tests in equipment technologies under development. The objective is to select and configure a set of component or subsystem tests such that system-level reliability is demonstrated with a specified confidence, while minimizing both cost and execution time. The formulation integrates test precedence constraints and Bayesian reliability estimation based on test outcomes. The NSGA-II algorithm is adapted to efficiently explore the space of feasible test plans, ensuring scalability and the ability to handle realistic constraints. The proposed framework contributes to the methodological robustness and practical applicability of intelligent test planning under uncertainty.