ABSTRACT
The purpose of this chapter is to explore the dependence of blood bank supply chain inventory organization using Boolean function techniques that evaluate subsystem failure and repair rates and vector genetic algorithms. We are currently developing a widespread network optimization model for the multifaceted supply chain of human being blood, a fresh product that saves lives. In exacting, the entire organization consists of six parts. The first part of the organization is a material input blood collection site. The second part of the system is the blood input blood center. The third part of the system is processing blood storage. The fourth part of the system is blood delivery center services. The fifth part of the system is the blood bank medical center. The sixth part of the system is blood bank hospital delivery to the customer. These are connected in a six-part series. The author has used the blood supply chain for Boolean functions to evaluate the efficiency of the thought system using a vector-evaluated genetic algorithm (VEGA). The reliability of each component obtained in three different cases is represented by R if the failure rate follows the Weibull time distribution and the failure follows the exponential time distribution. We have proposed an inventory policy for GA (VEGA) for blood storage suppliers in the blood supply chain. We too simulate models intended to gauge the performance of directorial strategy. Evaluation of the future algorithm for the vector using genetic stock (VEGA) and current stock determines the most favorable product quantity at the time of arrangement. Simulation results suggest that VEGA, is an effective method for managing the storage of blood storage facilities and blood supply chains.
