A new methodology for the reliability optimization of a k dissimilar-unit nonrepairable cold-standby redundant system is introduced in this paper. Each unit is composed of a number of independent components with generalized Erlang distributions of lifetimes arranged in a series-parallel configuration. We also propose an approximate technique to extend the model to the general types of non-constant hazard functions. To evaluate the system reliability, we apply shortest path technique in stochastic networks. The purchase cost of each component is assumed to be an increasing function of its expected lifetime. There are multiple component choices with different distribution parameters available for being replaced with each component of the system. The objective of the reliability optimization problem is to select the best components, from the set of available components, to be placed in the standby system in order to minimize the initial purchase cost of the system, maximize the system MTTF (mean time to failure), minimize the system VTTF (variance of time to failure) and also maximize the system reliability at the mission time. The goal attainment method is used to solve a discrete-time approximation of the original problem.
Azaron et al. REF proposed a new methodology for the reliability optimization of a k dissimilar-unit (or heterogeneous) nonrepairable coldstandby redundant VMs and applied the shortest path technique in stochastic networks to evaluate the reliability.
A multi-objective discrete reliability optimization problem for dissimilar-unit standby systems
OR Spectrum
Computer Science Mathematics