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Title: Applications of the Internet of Things and optimization to inventory and distribution management
Author: Raba Sánchez, David
Director: Juan, Angel A.  
Riera Terrén, Daniel  
Abstract: This thesis is part of the IoFEED (EU funded) project, which aims to monitor approximately 325 farm bins and investigates business processes carried out between farmers and animal feed producers. We propose a computer-aided system to control and optimize the supply chain to deliver animal feed to livestock farms. Orders can be of multiple types of feed, shipped from multiple depots using a fleet of heterogeneous vehicles with multiple compartments. Additionally, this case considers some business-specific constraints, such as product compatibility, facility accessibility restrictions, prioritized locations, or bio-security constraints. A digital twin based approach is implemented at the farm level by installing sensors to remotely measure the inventories. This thesis also embraces these sensors' design and manufacturing process, seeking the required precision and easy deployability at scale. Our approach combines biased-randomization techniques with a simheuristic framework to make use of data provided by the sensors. The analysis of results is based on these two real pilots, and showcases the insights obtained during the IoFEED project. The results of this thesis show how the Internet of Things and simulation-based optimization methods combine successfully to optimize deliveries of feed to livestock farms.
Keywords: vehicle routing problem
inventory routing problem
Internet of things
livestock farming
Document type: info:eu-repo/semantics/doctoralThesis
Version: info:eu-repo/semantics/publishedVersion
Issue Date: 17-Sep-2021
Publication license:  
Appears in Collections:Tesis doctorals

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