Open AccessTwo metaheuristics for solving the reliability redundancy allocation problem to maximize mean time to failure of a series–parallel system
Author(s) -
Amir Abbas Najafi,
Hamid Karimi,
Amirhossain Chambari,
Fatemeh Azimi
Publication year - 2013
Publication title -
scientia iranica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.299
H-Index - 51
eISSN - 2345-3605
pISSN - 1026-3098
DOI - 10.1016/j.scient.2012.12.022
Subject(s) - metaheuristic , simulated annealing , redundancy (engineering) , computer science , mathematical optimization , computation , monte carlo method , reliability (semiconductor) , genetic algorithm , algorithm , mathematics , power (physics) , statistics , physics , quantum mechanics , operating system
The redundancy allocation problem is one of the main branches of reliability optimization problems. Traditionally, the redundancy allocation model has focused mainly on maximizing system reliability at a predetermined time. Hence, in this study, we develop a more realistic model, such that the mean time to failure of a system is maximized. To overcome the structural complexity of the model, the Monte Carlo simulation method is applied. Two metaheuristics, Simulated Annealing (SA) and Genetic Algorithm (GA), are proposed to solve the problem. In addition, the design of experiments and response surface methodology are employed for tuning the GA and SA parameters. The metaheuristics are compared, based on their computation time and accuracy, in 30 test problems. Finally, the results are analyzed and discussed, and some conclusions are drawn