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|Title:||Optimization of complex system reliability by a modified great deluge algorithm||Authors:||Ravi, V.||Keywords:||Ant colony optimization
Improved non-equilibrium simulated annealing
Modified great deluge algorithm (MGDA)
Optimal redundancy allocation
Simulated annealing algorithm
|Issue Date:||Dec-2004||Citation:||Ravi, V. (2004-12). Optimization of complex system reliability by a modified great deluge algorithm. Asia-Pacific Journal of Operational Research 21 (4) : 487-497. ScholarBank@NUS Repository. https://doi.org/10.1142/S0217595904000357||Abstract:||In this paper, a global optimization meta-heuristic, the great deluge algorithm, is extended and applied to optimize the reliability of complex systems. Two different kinds of optimization problems (i) Reliability optimization of a complex system with constraints on cost and weight (ii) Optimal redundancy allocation in a multi-stage mixed system with constraints on cost and weight are solved to demonstrate the effectiveness of the algorithm. A software developed in ANSI C, implements the algorithm. In terms of both accuracy and speed, it is observed that the present algorithm, the modified great deluge algorithm (MGDA) yielded far superior results compared to those obtained by the simulated annealing, the improved non-equilibrium simulated annealing and other optimization algorithms. Further, when both accuracy and speed are considered simultaneously, both MGDA and another meta-heuristic, ant colony optimization (ACO) yielded comparable results. In conclusion, the MGDA, can be used as an efficient alternative to AGO and other existing optimization techniques.||Source Title:||Asia-Pacific Journal of Operational Research||URI:||http://scholarbank.nus.edu.sg/handle/10635/132758||ISSN:||02175959||DOI:||10.1142/S0217595904000357|
|Appears in Collections:||Staff Publications|
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