MPC approach for synchronized supply chains of perishable goods

MPC approach for synchronized supply chains of perishable goods

Hipolito, Tomas (University of Lisbon)
Lemos Nabais, Joao (Polytechnical Institute of Setubal)
Carmona Benitez, Rafael (Universidad Anahuac Mexico Norte)
Ayala Botto, Miguel (University of Lisbon)
Negenborn, R.R. (TU Delft Transport Engineering and Logistics)

Bousonville, Thomas (editor)
Melo, Teresa (editor)
Rezg, Nidhal (editor)
Vernadat, François (editor)

2017

The movement of perishable goods is growing worldwide. Perishable goods need to be available to the market before the expiration date. With the decrease in inventory levels the components of a supply chain become even more integrated and dependent on coordinated decisions. Information regarding perishable goods must be visible throughout the supply chain for avoiding goods loss. A Model Predictive Control (MPC) heuristic to address operations management at supply chains of perishable goods is proposed in this paper. The approach is capable to follow the remaining time until expiration date which is critical to avoid losses. The supply chain is modeled using a state-space representation and operations management at the supply chain is formulated as anMPC Problem. In order to cope with operational decisions, the problem is solved on a periodic basis. The proposed approach is capable to deal with production decisions, monitor work-in-progress (WIP), and make transport assignments while monitoring the remaining time until the expiration date. Flows over the supply chain can be synchronized and therefore we named this type of supply chain a Synchronized Supply Chain (SSC). The approach is modular and easily scalable for largescale supply chains. Numerical results illustrate these statements.

http://resolver.tudelft.nl/uuid:aef013e2-3a52-4bca-a254-ae3fe9bca878

Saarland University of Applied Sciences, Saarbrücken, Germany

Proceedings of the 7th International Conference on Industrial Engineering and Systems Management (IESM 2017)

IESM 2017: 7th International Conference on Industrial Engineering and Systems Management, 2017-10-11 → 2017-10-13, Saarbrücken, Germany

Institutional Repository

conference paper

© 2017 Tomas Hipolito, Joao Lemos Nabais, Rafael Carmona Benitez, Miguel Ayala Botto, R.R. Negenborn