IEEE Transactions on Systems, Man and Cybernetics - Special issue on artificial intelligence
Neuro-Dynamic Programming
Rollout Algorithms for Combinatorial Optimization
Journal of Heuristics
Rollout Algorithms for Stochastic Scheduling Problems
Journal of Heuristics
Expected-Value Analysis of Two Single Fault Diagnosis Algorithms
IEEE Transactions on Computers
Computational Complexity Issues in Operative Diagnostics of Graph-Based Systems
IEEE Transactions on Computers
Algorithms for sequential fault diagnosis
Algorithms for sequential fault diagnosis
Operative diagnosis of graph-based systems with multiple faults
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Rollout strategies for sequential fault diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Multiple fault diagnosis (MFD) is used as an effective measure to tackle the problems of real-shop floor environment for reducing the total lifetime maintenance cost of the system. It is a well-known computationally complex problem, where computational complexity increases exponentially as the number of faults increases. Thus, warrants the application of heuristic techniques or AI-based optimization tools to diagnose the exact faults in real time. In this research, rollout strategy-based probabilistic causal model (RSPCM) has been proposed to solve graph-based multiple fault diagnosis problems. Rollout strategy is a single-step iterative process, implemented in this research to improve the efficiency and robustness of probabilistic causal model. In RSPCM instead of finding all possible combinations of faults, collect the faults corresponding to each observed manifestations that can give the best possible result in compared to other methods. Intensive computational experiments on well-known data sets witness the superiority of the proposed heuristic over earlier approaches existing in the literature. From experimental results it can easily inferred that proposed methodology can diagnosed the exact fault in the minimum fault isolation time as compared to other approaches.