LAUSR

This paper proposes a new multiobjective multiple stage reliability growth planning (MO-MS-RGP) model. The model is based on multiobjective consideration of developing a new product, including the cost, time, and product reliability. The number of test units, test time, and the percentage of introduced new technologies are considered as decision variables in the model. Varying reliability growth rates are considered for each subsystem in each stage. Product new technologies or contents can be completely introduced in one stage or partially introduced to the product over multiple stages. New product development time limit and budget are considered as constraints in the MO-MS-RGP model. An integrated approach is developed to formulate and solve the proposed MO-MS-RGP problem. The approach starts with a multiobjective evolutionary algorithm, called multipleobjective particle swarm optimization to find a set of Pareto optimal solutions. Then, clustering methods are applied to cluster the solutions obtained by the evolutionary algorithm. Finally, the clustered solutions are ranked using a multiple criteria decision making method. A numerical example illustrates the application of the proposed MO-MS-RGP model for the reliability growth planning optimization of a next generation engine development.