SmartPhone Stock Optimization using Pulp Library
A case study was created in order to explain what an optimization problem looks like and how to solve it using Pulp python library
Here is the Case study
Say we are hired as data analysts to a smartphone e-commerce company that sells two major brands of smartphones: Samsung and Apple. The company currently has a naive dynamic pricing strategy where it consistently changes the same phone's prices throughout the day. The company would like to know if there decide on a fixed price, how much of each of the brands they need to stock, and if it makes sense to stick to their naive dynamic pricing, i.e. if it maximizes revenue given the constraint?
Here is the code to solve the business case and the article that explains it