RAP via hybrid genetic simulating annealing algorithm

This paper aims to solve Redundancy allocation problem (RAP). It is a significant complex optimization and non-linear integer programming problem of reliability engineering. RAP includes the choices of components and the suitable amount of redundant subsystems for maximizing reliability of the system under given restrictions like cost, weight, volume etc. It is difficult to solve non-linear complex problems. In this paper, the RAP is solved by the combination of genetic and simulating algorithm that is called Hybrid Genetic Simulating Annealing Algorithm (HGSAA). It can be observed that superiority of both the algorithms are combined and form an adequate algorithm which ignores the individual weakness. Comparative analysis of HGSAA with existing methods such as Heuristic Algorith, Constraint Optimization Genetic Algorithm, Hybrid Particle Swarm Optimization and Constraint Optimization Genetic Algorithm are presented in this study. RAP is also solved by Branch and Bound method to validate the result of HGSAA. The developed algorithm is programmed by Matlab.