Abstract
Transmission quality of a communication/computer system is a high-level objective of system supervisors. Therefore, transmission reliability improvement or optimization is an important issue for many organizations. One way to maximize transmission reliability is to model the system as a stochastic communication network including arcs and nodes and then determine the optimal component redundancy allocation. However, modern components are highly reliable. Thus, a decision maker may be more concerned about cost than reliability. This article considers cost-oriented component allocation subject to a reliability threshold and correlated failures characterized by a correlated binomial distribution model. To solve this problem, we employ a genetic algorithm to search for the optimal component redundancy allocation possessing minimal allocation cost. The computational efficiency of the genetic algorithm-based method is demonstrated through several benchmark networks and compared against several popular soft computing algorithms.