How can machine learning improve supply chain and logistics? Marine Startups

According to McKinsey Global Institude study on impact of AI and automation, transportation and warehousing are one of the most automatable sectors of economy (3rd place), with 60% potential for automation. Predicting the future demands for production and supplies, improving transportation routines, or automating physical inspection and maintenance are some of vast possibilities to use data science in supply chain management. While self-driving cars seem to be a future of transport, we would like to focus on optimizing "here and now", without changing the market – just with smart, data-driven decisions. We would like to focus on a problem of choosing location of warehouse to minimise cost of both freight and warehouse maintenance. It is a complex Data Science problem, that is composed of various independent components that need to be optimised.