Robust metaheuristic algorithm for redundancy optimization in large-scale complex systems

Research output: Contribution to journalArticle

5 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)209-228
Number of pages20
JournalAnnals of Operations Research
Volume133
Issue number1-4
DOIs
Publication statusPublished - 2005 Jan 1

Fingerprint

Complex systems
Redundancy
Metaheuristics
Methodology
Tabu search
System reliability
Optimization problem
Robustness

Keywords

  • Complex system
  • Metaheuristic
  • Redundancy
  • Reliability
  • Tabu search

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Decision Sciences(all)

Cite this

Robust metaheuristic algorithm for redundancy optimization in large-scale complex systems. / Ryoo, Hong Seo.

In: Annals of Operations Research, Vol. 133, No. 1-4, 01.01.2005, p. 209-228.

Research output: Contribution to journalArticle

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