Abstract
With the increase in system complexity, the intelligent heuristic optimization methods have received more and more attention on system reliability analysis. However, the objective functions and constraint conditions of system reliability are nonlinear. Thereby, a hybrid optimization method was proposed, based on the shuffled frog leaping algorithm and bacterial foraging algorithm, to solve the problem of system reliability and redundancy allocation. First, random grouping strategy was added to maintain the diversity of the population. Then, the Levy flight update strategy was used to increase the global search ability. Finally, the method of migration operation was introduced to escape from local optimums. The proposed methodology, a new version of the SFLA algorithm, was then applied to the mathematical test and the operation of the system reliability model, respectively. Results show that compared to the common methods, it can obtain the best solution, with the maximum value of the system reliability.
Highlights
The system reliability refers to the system ability of performing the required function under prescribed conditions and within the stipulated time
The complex system reliability optimization is aimed to obtain the highest reliability with seeking a best design scheme in some resource-constraint conditions, or to achieve maximum economic benefits and minimizing investment with meeting the requirements of a certain reliability index
Orouji et al indicated that the shuffled frog leaping algorithm has the best capability and most efficiency among other well-developed algorithms such as the genetic algorithm (GA), harmony search (HS), particle swarm optimization and simulated annealing (SA), with 3.97, 0.03, 0.33 and 0.08% improvement in obtained objective function values, respectively [13, 14]
Summary
The system reliability refers to the system ability of performing the required function under prescribed conditions and within the stipulated time. The appearance and development of intelligent algorithm have been provided a new tool to solve the problem of system reliability optimization. The great development of the meta-heuristic optimization techniques represents the impetus for utilizing shuffled frog leaping algorithm to identify the unknown parameters of the single-diode PV model [10]. Orouji et al indicated that the shuffled frog leaping algorithm has the best capability and most efficiency among other well-developed algorithms such as the genetic algorithm (GA), harmony search (HS), particle swarm optimization and simulated annealing (SA), with 3.97, 0.03, 0.33 and 0.08% improvement in obtained objective function values, respectively [13, 14]. The detail descriptions will be narrated in the fourth part
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