System Reliability Maximization for Stochastic-Flow Network Subject to Total lead-time based on Random Weighted Genetic Algorithm
System reliability is an important performance index for many real-life systems, such logistic information system, electric power systems, computer systems and transportation systems. These systems can be modelled as stochastic-flow networks (SFNs) composed of arcs and nodes. In this paper, we investigate components assignment problem for stochastic flow networks subject to two constraints namely total lead-time, and system reliability. A new approach based on random weighted genetic algorithm (RWGA) is proposed for searching an optimal components assignment which leads to maximizing system reliability and minimizing total lead time. The results revealed that an optimal components assignment leads to the maximum reliability and minimum total lead-time using the proposed approach.
Keyword - Component Assignment Problem, Genetic Algorithm, Lead-Time, System Reliability.