Logistic Intelligence and Decision Making

It does not require previous knowledge, although some operational research and Information Technology basis are relevant.

Given the applied character of the proposed themes, expository methodologies are promoted, altogether with the respective practical application.

Current logistics systems are strongly influenced by conflicting interests, and characterized by multiple factors of a complex system.
It is in this context that the manager of a logistics system acts, being regularly asked to make decisions.

Thus, the main objectives of this Course Unit are:
O1 – analyze and apply optimization and decision techniques aimed at logistics;
O2 – use decision analysis models in logistics
O3 – analyze the main advances of Artificial Intelligence at the service of logistics (including sensors, automated processes and blockchain)
O4 – know techniques for handling large amounts of data, and their integration into artificial intelligence systems.

It is intended that the student demonstrates the competencies and skills to:
C1 – analyze optimization and decision models aimed at logistics
C2 – analyze and discuss the solutions generated and their implications for logistics
C3 – recognize automated artificial intelligence systems with application in logistics.

1 – Planning and optimization in logistics
1.1 – Optimization of resources
1.2 – Vehicle routes and supply chain
1.3 – Facility location
1.4 – Production planning
1.5 – Shift scheduling and rostering
2 – Decision-making in logistics
2.1 – Decision making process
2.2 – Decision trees
2.3 – Sensitivity analysis
2.4 – Utility theory
2.5 – Decision-making applied to supply chain management
3 – Technologies in logistics
4 – Digital transformation in logistics
4.1 – Robotic process automation
4.2 – Blockchain
4.3 – IoT, Cloud and Big data
4.4 – Artificial intelligence applied to logistics.

NAO

– de Carvalho, J. M. C., & Cardoso, E. G. (2002). Logística. Sílabo.

– Jacobs, F. R., Chase, R. B., & Lummus, R. R. (2014). Operations and supply chain management. NewYork, NY: McGraw-Hill/Irwin.

– Langley, C. J., Novack, R. A., Gibson, B., & Coyle, J. J. (2020). Supply chain management: a logistics perspective.Cengage Learning.

– Manners-Bell, J., & Lyon, K. (2019). The logistics and supply chain innovation handbook: Disruptive technologies and new business models. Kogan Page Publishers.

– Subramanian, N., Chaudhuri, A., & Kayıkcı, Y. (2020). Blockchain and Supply Chain Logistics: Evolutionary Case Studies. Springer Nature.

– Sullivan, M., & Kern, J. (2021). The Digital Transformation of Logistics: Demystifying the Impacts of the Fourth Industrial Revolution. New Jersey, Wiley, IEEE Press.