AI-BIPTO (Artificial Intelligence Boosted Integrated Production and Transport Optimization)

Motivation and goals: In the compound feed industry the production and transport are nowadays closely intertwined. Failing to integrate the production and transport schedules leads to excessive production and transportation costs. Moreover, it leads to extra unnecessary CO2 emission of both production and transport. To address this common practical problem, this project focuses on the following research goals:

1. The development of models and solution methods for integrated production and transport
   scheduling that are efficient, scalable, and robust against the omnipresence of uncertainty in the
   processes.
2. The design and development of a Proof-of-Concept (PoC) planning tool for integrated production and
   transport scheduling, validated in the compound feed industry as a use case.
3. The establishment of a new Community of Practice, consisting of representatives from academia and
   different industry application domains, facing the problem of integrating production and transport schedules.