Abstract:
To run a successful business all the processes within a business should be managed
efficiently and some more than the others. One such process is inventory management. In
the hotel industry this important as having the right amount of inventory items plays a
major role in satisfying the customers. Inventory management has is done mainly by using
conventional techniques such as EOQ, periodic review policy and optional replacement
policy.
This project is mainly focused on developing a model using machine learning
which will help in efficiently managing this process by predicting the amount inventory
required for next month. To accomplish this a dataset of closing inventory values was
obtained from a reputed hotel in Sri Lanka. Using neural networks and SVR a hybrid
model was developed to accomplish this task.
