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Robust Modeling to Improve Reliability in Series-Parallel Systems with Redundancy Allocation

Ghaffarian Salehi Nezhad, Ali | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43414 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Eshraghniaye Jahromi, Abdolhamid
  7. Abstract:
  8. In general, reliability is the ability of a system to perform and maintain its functions in routine circumstances, as well as hostile or unexpected circumstances. Redundancy Allocation Problem (RAP) is a combinatorial problem where it is going to maximize system reliability by discrete selection from available components. The main purpose of this study is to prove the effectiveness of robust optimization to solve RAP. Generally, robust optimization is a field of optimization theory where robustness is sought against uncertainty and/or variability of parameters' values. In this study it is assumed to have Erlang distribution density for components' failures where to implement robust optimization. Another assumption is that each subsystem can have one of cold-standby or active redundancy strategies. Noticeably, the RAP is a NP-Hard problem which cannot be solved in reasonable time using exact optimization techniques. Therefore, an approach in which an Ant Colony optimization (ACO) algorithm as meta-heuristic phase and three other heuristics are combined to develop a solving methodology for RAP which result in appropriate solutions.

  9. Keywords:
  10. Series-Parallel System ; Heuristic Algorithm ; Ant Colony Algorithm ; Reliability Optimization ; Robust Optimization ; Redundancy Allocattion Problem

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