Optimal Diagnosis Procedures for k-out-of-n Structures
IEEE Transactions on Computers
Heuristic least-cost computation of discrete classification functions with uncertain argument values
Annals of Operations Research
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Discrete Applied Mathematics - Special issue on the satisfiability problem and Boolean functions
Data Structures, Algorithms, and Software Principles
Data Structures, Algorithms, and Software Principles
Diagnosing double regular systems
Annals of Mathematics and Artificial Intelligence
RanGen: A Random Network Generator for Activity-on-the-Node Networks
Journal of Scheduling
Optimal testing algorithms for symmetric coherent systems.
Optimal testing algorithms for symmetric coherent systems.
Scheduling Markovian PERT networks to maximize the net present value
Operations Research Letters
TestAnt: An ant colony system approach to sequential testing under precedence constraints
Expert Systems with Applications: An International Journal
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We study the problem of sequentially testing the components of a multi-component system to learn the state of the system, when the tests are subject to precedence constraints and with the objective of minimizing the expected cost of the inspections. Our focus is on k-out-of-n systems, which function if at least k of the n components are functional. A solution is a testing policy, which is a set of decision rules that describe in which order to perform the tests. We distinguish two different classes of policies and describe exact algorithms (one branch-and-bound algorithm and one dynamic program) to find an optimal member of each class. We report on extensive computational experiments with the algorithms for representative datasets.