Distributed Environment of Machine Learning with Optional Privacy Preserving for Supply Chain Management

This thesis deals with intricate challenges faced in supply chain collaboration among multiple parties while safeguarding their sensitive information. So our primary focus revolves around optimizing the complexities of last mile delivery, a crucial aspect of contemporary logistics that involves multiple participants and the transportation of various categorized goods. This research does a substantial contribution to the field of supply chain management, offering practical and innovative solutions that are tailored to the contemporary landscape of logistics and distribution.