Please use this identifier to cite or link to this item: https://doi.org/10.1142/S0217595904000357
Title: Optimization of complex system reliability by a modified great deluge algorithm
Authors: Ravi, V. 
Keywords: Ant colony optimization
Complex systems
Global optimization
Improved non-equilibrium simulated annealing
Meta-heuristics
Modified great deluge algorithm (MGDA)
Optimal redundancy allocation
Reliability
Simulated annealing algorithm
Issue Date: Dec-2004
Source: 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
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