Logistics System Utilizing Reinforcement Learning to Optimize Shipping Costs for Food Welfare Facilities - A Temporary Solution in a Trial Environment -

情報処理学会

この論文をさがす

説明

This paper presents our logistics system project which is being implemented for a food welfare organization called "Foodbank" in Japan to optimize their resources in shipping costs. The project employs SARSA algorithm from the reinforcement learning field of machine learning as its core functionality. In this study, the agent aims to acquire its optimal policy for delivering foods to respective food welfare facilities via the shortest possible distance. Currently, the agent can find its optimal policy in a small environment, but the environment will be expanded with other constraints subsequently. Our project is a creative example of finding the best result from limited resources.

収録刊行物

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ