A study on the relaxed linear programming bounds method for system reliability

Abstract The linear programming (LP) bounds method was applied for computing bounds on the system reliability of general systems based on the individual component state probabilities and joint probabilities of the states of a small number of components. In the LP bounds method, the bounds of the system reliability can be obtained by using LP. These bounds are useful approximations when exact solutions are costly or unavailable. However, the size of the LP problem determined by the number of design variables and the number of constraints increases exponentially with the number of components. This size problem is the main drawback of the LP bounds method. This paper presents a relaxed linear programming (RLP) bounds method to overcome this drawback of the LP bounds method. The accuracy and efficiency of the RLP bounds method are investigated using numerical examples involving series and parallel systems.