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Redundancy Optimization In Multi-Level System Using Meta-Heuristics

In: Recent Advances In Stochastic Operations Research II

Author

Listed:
  • IL HAN CHUNG

    (Technical Research Institute, Hyundai Rotem Company, 462-18, Sam-Dong, Uiwang-Shi, Gyunggi-Do, 449-910, Korea)

  • WON YOUNG YUN

    (Department of Industrial Engineering, Pusan National University, 30 Changjeon-Dong, Kumjeong-Ku, Busan 609-735, Korea)

  • HO GYUN KIM

    (Department of Industrial and Management Engineering, Dong-Eui University, Busanjin-Ku, Busan, 614-714, Korea)

Abstract

Single-level systems have been considered in redundancy allocation problems. Traditionally, we assume typical structures, for example, series, k-out-of-n, series-parallel, and determine how many redundant units should be assigned to each unit in the system structure. In regard to system reliability, it is most effective to duplicate the lowest level objects, because parallel-series systems are more reliable than series-parallel systems. However, it may not be the most cost effective way. In this paper, redundancy is considered at all levels in a series system with multi-levels, and a mixed integer programming model is formulated. Some meta-heuristics (genetic algorithm, simulated annealing, and ant colony algorithm) are considered to solve the problem and some examples are studied.

Suggested Citation

  • Il Han Chung & Won Young Yun & Ho Gyun Kim, 2009. "Redundancy Optimization In Multi-Level System Using Meta-Heuristics," World Scientific Book Chapters, in: Tadashi Dohi & Shunji Osaki & Katsushige Sawaki (ed.), Recent Advances In Stochastic Operations Research II, chapter 13, pages 183-199, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812791672_0013
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