Author(s)

Essa Abrahim Abdulgader Saleem^*, Thien-My Dao, Zhaoheng Liu

Department of Mechanical/Manufacturing Engineering, école de Technologie Supérieure, Montreal, Canada.

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 the RRAP 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.

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

Saleem, E. , Dao, T. and Liu, Z. (2018) Multiple-Objective Optimization and Design of Series-Parallel Systems Using Novel Hybrid Genetic Algorithm Meta-Heuristic Approach. World Journal of Engineering and Technology, 6, 532-555. doi: 10.4236/wjet.2018.63032.