This invention discloses a method for automatically generating
pharmacy outbound tasks based on a driver-driven approach, belonging to the field of pharmaceutical
logistics management. It includes receiving and aggregating
drug shortage requests from various pharmacies, calculating the proportion of
drug shortages reflecting replenishment urgency, and then collecting inventory attributes such as
drug unit price, days in stock, and
expiration date. Priority scores are calculated by combining weighted factors of 50% for the proportion of drug shortages, 30% for
expiration date or
stocking time, and 20% for the unit price. When generating tasks, the
system follows the principles of prioritizing
expiration date, consistent unit price, and
stocking time, and performs sub-task splitting for batches with different unit prices to solve the problem of confusing unit price management at the
pharmacy level. The generated tasks are proactively pushed to mobile devices or smart shelves with gravity sensors, utilizing automatic weight and quantity conversion to achieve closed-loop management of accurate picking monitoring, anomaly alarms, and automatic inventory
verification. This invention realizes intelligent driving of replenishment tasks, reduces the risk of manual omissions, and improves picking accuracy and
management efficiency.