Before a grocery store opens key operational decisions must be made with no historical data. One important decision is how to optimally lay out the store to maximize consumer spending. This work reviews existing literature on simulation to optimize grocery store layout, uses computer vision techniques to transform a store diagram into a digital representation, and applies simulation methods to approximate which of the layouts proposed by a store designer would result in the highest amount of impulse purchasing. Output analysis methods are used to compare these results to determine whether one design outperforms the others.

Navigate to this repository in the command line. Use
pip install .
to install the grocerypathsim package. Installing jupyter is recommended as well in order to view the Usage notebook.
Additionally, tesseract must be installed for OCR.
Mac
brew install tesseract

Linux
sudo apt update
sudo apt install tesseract-ocr
sudo apt install libtesseract-dev

See Usage.ipynb for examples and directions on how to use this package.
In order to use the 2017 Instacart Grocery Shopping Dataset the necessary files must first be downloaded and placed in the same directory with the filenames "departments.csv", "products.csv", and "order_products__train.csv". Otherwise, create a different dataset and generator for grocery lists in shopping_lists.py.