Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms
Reliability of grid service systems
Computers and Industrial Engineering
A knowledge management system for series-parallel availability optimization and design
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Optimal multilevel redundancy allocation in series and series-parallel systems
Computers and Industrial Engineering
Reliability of grid service systems
Computers and Industrial Engineering
Reliability analysis of waste clean-up manipulator using genetic algorithms and fuzzy methodology
Computers and Operations Research
Reliability analysis of complex multi-robotic system using GA and fuzzy methodology
Applied Soft Computing
Computers and Operations Research
Multilevel redundancy allocation using two dimensional arrays encoding and hybrid genetic algorithm
Computers and Industrial Engineering
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Single-level systems have been considered in redundancy allocation problems. It may be the best policy in some specific situations, but not in general. In regards to reliability, it is most effective to duplicate the lowest objects, because parallel-series systems are more reliable than series-parallel systems. However, the smaller an object is, the more time and higher accuracy are needed for duplicating it, and so, redundancy cost can be decreased by using modular redundancy. Therefore, providing redundancy at high levels like as modules or subsystems, can be more economical than providing redundancy at low level of components. In this paper, the problem in which redundancy is available at all levels in a series system is addressed and a mixed integer programming model is presented. A heuristic algorithm and a genetic algorithm are proposed to solve the problem and some examples illustrate the procedure.