Using a genetic algorithm to optimize supply chain decisions
This repository contains a Python program (in both .ipynb and .py fomat) that explores how effective various genetic and natural algorthims are at finding an optimal or near optimal solution for supply chain decisions. Specifially, we wish to minimize the cost of supplying goods to a set of retail locations given a set of factory/warehouse locations. Demand by item-type and straight line distance drive the cost function used for optimization.
Brian Reid Thomas Clunie