An ant colony algorithm for the sequential testing problem under precedence constraints.

We consider the problem of minimum cost sequential testing of a series (parallel) system under precedence constraints that can be modeled as a nonlinear integer program. We develop and implement an ant colony algorithm for the problem. We demonstrate the performance of this algorithm for special type of instances for which the optimal solutions can be found in polynomial time. In addition, we compare the performance of the algorithm with a special branch and bound algorithm for general instances. The ant colony algorithm is shown to be particularly effective for larger instances of the problem

Sequential testing of series parallel systems

In this thesis, we study the sequential testing problem of 3-level deep Series Parallel systems (SPS). We assess the performance of depth-first permutation (DFP) algorithm that has been proposed in the literature. DFP is optimal for 1-level deep, 2-level deep SPSs and 3-level deep SPSs that consist of identical components. It can be used to test general SPSs. We report the first computational results regarding the performance of DFP for 3-level deep SPSs by comparing its performance with a dynamic version of DFP and a hybrid simulated annealing-tabu search algorithm that we developed. In order to implement the algorithms, we propose an efficient method to compute the expected cost of a permutation strategy. The results of computational experiments for this algorithm and other algorithms proposed in the literature are reported

Testing strategies for k-out-of-n systems under forest type precedence constraints

This thesis investigates diagnosis strategies for k-out-of–n systems under precedence constraints. A k-out-of-n system consists of n independent components whose working probabilities of are known in advance. The system itself functions if at least k components function. The true state of the system is determined by the sequentially inspection of these components. This inspection is costly and the cost of inspection for each component is also known. This study aims to minimize expected cost of determining true state of such a system when there are forest type precedence constraints. Optimal inspection strategies are already known for series and parallel systems. In this study, modifications of these strategies are proposed for k-out-of-n systems. Numerical results are presented to evaluate and compare the proposed strategies