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https://doi.org/10.1109/TSMCA.2006.889476

has been cited by the following article:

• TITLE: Multiple-Objective Optimization and Design of Series-Parallel Systems Using Novel Hybrid Genetic Algorithm Meta-Heuristic Approach

  AUTHORS: Essa Abrahim Abdulgader Saleem, Thien-My Dao, Zhaoheng Liu

  KEYWORDS: Multi-Objective Optimization, Reliability-Redundancy Allocation, Overspeed, Gas Turbine, Hybrid Genetic Algorithm

  JOURNAL NAME: World Journal of Engineering and Technology, Vol.6 No.3, June 12, 2018

  ABSTRACT: In this study, we develop a new meta-heuristic-based approach to solve a multi-objective optimization problem, namely the reliability-redundancy allocation problem (RRAP). Further, we develop a new simulation process to generate practical tools for designing reliable series-parallel systems. Because theRRAP is an NP-hard problem, conventional techniques or heuristics cannot be used to find the optimal solution. We propose a genetic algorithm (GA)-based hybrid meta-heuristic algorithm, namely the hybrid genetic algorithm (HGA), to find the optimal solution. A simulation process based on the HGA is developed to obtain different alternative solutions that are required to generate application tools for optimal design of reliable series-parallel systems. Finally, a practical case study regarding security control of a gas turbine in the overspeed state is presented to validate the proposed algorithm.