SupplyChainv0_gym

Reinforcement Learning for Optimal inventory policy

SupplyChainReinforcement

Supply Chain Reinforcement Learning

SupplyChainReinforcement-SCM-RL

value-at-risk

A notebook exploring the value at risk metric for portfolio analysis.

Supply-Chain-Optimization

The United States Agency for International Development (USAID, usaid.gov) is an independent agency from the U.S. federal government that is a leader in supporting the developing countries around the world in terms of education, economy, health, agriculture and many other fields. One of the Agency’s biggest projects is supply of medicine commodities to more than 60 countries around the globe. For the past couple of years USAID have been under the attention of the public due to the constant delay of deliveries in their supply chain. In 2016 only, the organization signed a contract with a supplier for $9.5 billion but faced a lot of criticism since the agency published that 30-50% of medicine deliveries arrived later than planned. Delayed deliveries can increase the supply chain costs for USAID as that will increase their storage needs for storing excess inventory, but more importantly, can disrupt a patient’s treatment, or potentially cause a loss of life. The solution for this problem can be a machine learning model - a combination of a classifier and a regressor, that will predict if a specific delivery in the supply chain of USAID is going to be delayed, and after that forecast the delay time of a potential delayed delivery. This can assist USAID’s representatives around the world in planning accordingly for a particular delivery arrival and make the necessary changes in order to prevent the possible side-effects.