A fuzzy-based prediction approach for blood delivery using machine learning and genetic algorithm

Multiple diseases require a blood transfusion on daily basis. The process of is successful when the type and amount available transported at right time from bank to operating room. Blood distribution has large portion cost in hospital logistics. can serve various hospitals; however, limited due donor shortage. transportation must handle several requirements such as timely delivery, vibration avoidance, temperature maintenance, keep usable. In this paper, we discuss first section issues with delivery constraint. second present routing scheduling system based artificial intelligence deliver blood-banks hospitals single multiple banks respect vehicle capacity used creating shortest path. third consist solution for predicting needs each history using machine learning fuzzy logic. last compare results well-known our cases shortage sudden changes.