OPTIMIZATION OF COMPLEX SYSTEM RELIABILITY BY A MODIFIED GREAT DELUGE ALGORITHM

Vadlamani Ravi ()
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Vadlamani Ravi: Institute of Systems Science, National University of Singapore, 25 Heng Mui Keng Terrace, Singapore 119615, Singapore

Asia-Pacific Journal of Operational Research (APJOR), 2004, vol. 21, issue 04, 487-497

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 ACO and other existing optimization techniques.

Keywords: Reliability; complex systems; global optimization; meta-heuristics; modified great deluge algorithm (MGDA); optimal redundancy allocation; ant colony optimization; simulated annealing algorithm; improved non-equilibrium simulated annealing (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (3)

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DOI: 10.1142/S0217595904000357

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