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Robust Metaheuristic Algorithm for Redundancy Optimization in Large-Scale Complex Systems

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  • Hong Ryoo

Abstract

Based upon the general tabu search methodology, this paper develops a robust metaheuristic algorithm for the redundancy optimization in large-scale complex system reliability that performs a rigorous search of the “attractive” feasible space and is capable of escaping from a local solution. An illustrative example is provided and extensive computational results are reported on two test problems from the literature (Aggarwal, 1976; Shi, 1987) and also on randomly generated large-scale instances of complex systems with up to 200 components. The computational results indicate that the proposed metaheuristic algorithm possesses a superior robustness and efficiency for solving the class of hard optimization problems studied in this paper. Copyright Springer Science + Business Media, Inc. 2005

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  • Hong Ryoo, 2005. "Robust Metaheuristic Algorithm for Redundancy Optimization in Large-Scale Complex Systems," Annals of Operations Research, Springer, vol. 133(1), pages 209-228, January.
    • Handle: RePEc:spr:annopr:v:133:y:2005:i:1:p:209-228:10.1007/s10479-004-5034-x
    DOI: 10.1007/s10479-004-5034-x
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    Cited by:

    1. Young Woong Park, 2020. "MILP Models for Complex System Reliability Redundancy Allocation with Mixed Components," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 600-619, July.

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