2025
Daniel Cuellar-Usaquén; Marlin W. Ulmer; Oliver Antons; Julia C. Arlinghaus
Dynamic multi-period recycling collection routing with uncertain material quality Journal Article
In: OR Spectrum, 2025, ISSN: 1436-6304.
Abstract | Links | BibTeX | Tags: Benchmarking, Buyer-Supplier Relationship, Circular Economy, Circular Supply Chain, Decision-making, Linear programming, Optimization, Sustainability
@article{Cuellar-Usaqu\'{e}n2025,
title = {Dynamic multi-period recycling collection routing with uncertain material quality},
author = {Daniel Cuellar-Usaqu\'{e}n and Marlin W. Ulmer and Oliver Antons and Julia C. Arlinghaus},
url = {https://www.ms.ovgu.de/Research/Data.html
https://www.ms.ovgu.de/ms_media/Downloads/Data_Dynamic_Multi_Period_Recycling_Collection_Routing-p-604.zip
https://rdcu.be/d9abe
},
doi = {10.1007/s00291-025-00808-z},
issn = {1436-6304},
year = {2025},
date = {2025-02-08},
urldate = {2025-02-08},
journal = {OR Spectrum},
publisher = {Springer Science and Business Media LLC},
abstract = {We consider the problem of collecting and processing waste material. At a production facility, a known amount of inventory is required for production (e.g., paper) for every period. Instead of new material, the facility relies on collected and processed waste material (e.g., paper waste). This material is collected from regional waste collection locations. The amount of waste material per location is uncertain, as is the quality of the collected waste, i.e., the resulting inventory when processing the material. If the inventory is insufficient at the end of a period, costly new material must be bought. Each period, decisions are made about how much waste material to collect from which location and how to route the collection vehicles accordingly. Ideally, inventory is built to hedge against quality uncertainty and to ensure efficient routing operations in future periods. We propose a stochastic lookahead method that samples a set of scenarios and solves a simplified two-stage stochastic program in every period. We show the value of our method for two case studies, one based on real-world data from Sachsen-Anhalt, Germany, and one from the literature with data from the United Kingdom. We further conduct a detailed analysis of our method and the problem characteristics. The results show that our method effectively anticipates all sources of uncertainty, reducing cost significantly compared to benchmark policies. This superior performance is due to appropriate state-dependent supplier selection that considers the percentage of material loss, available material, and routing cost for current and future periods.},
keywords = {Benchmarking, Buyer-Supplier Relationship, Circular Economy, Circular Supply Chain, Decision-making, Linear programming, Optimization, Sustainability},
pubstate = {published},
tppubtype = {article}
}
We consider the problem of collecting and processing waste material. At a production facility, a known amount of inventory is required for production (e.g., paper) for every period. Instead of new material, the facility relies on collected and processed waste material (e.g., paper waste). This material is collected from regional waste collection locations. The amount of waste material per location is uncertain, as is the quality of the collected waste, i.e., the resulting inventory when processing the material. If the inventory is insufficient at the end of a period, costly new material must be bought. Each period, decisions are made about how much waste material to collect from which location and how to route the collection vehicles accordingly. Ideally, inventory is built to hedge against quality uncertainty and to ensure efficient routing operations in future periods. We propose a stochastic lookahead method that samples a set of scenarios and solves a simplified two-stage stochastic program in every period. We show the value of our method for two case studies, one based on real-world data from Sachsen-Anhalt, Germany, and one from the literature with data from the United Kingdom. We further conduct a detailed analysis of our method and the problem characteristics. The results show that our method effectively anticipates all sources of uncertainty, reducing cost significantly compared to benchmark policies. This superior performance is due to appropriate state-dependent supplier selection that considers the percentage of material loss, available material, and routing cost for current and future periods.
2024
Luca Janecki; Oliver Antons; Daniel Reh; Julia C. Arlinghaus
Comparing Digital Twins and Virtual Engineering in Buyer Supplier Relationships for Complex Production Facilities Proceedings Article
In: Thürer, Matthias; Riedel, Ralph; Cieminski, Gregor; Romero, David (Ed.): Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments, pp. 180–193, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-71645-4.
Abstract | Links | BibTeX | Tags: Buyer-Supplier Relationship, Digital Twin, Production, Virtual Engineering
@inproceedings{10.1007/978-3-031-71645-4_13,
title = {Comparing Digital Twins and Virtual Engineering in Buyer Supplier Relationships for Complex Production Facilities},
author = {Luca Janecki and Oliver Antons and Daniel Reh and Julia C. Arlinghaus},
editor = {Matthias Th\"{u}rer and Ralph Riedel and Gregor Cieminski and David Romero},
url = {https://link.springer.com/chapter/10.1007/978-3-031-71645-4_13},
doi = {10.1007/978-3-031-71645-4_13},
isbn = {978-3-031-71645-4},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments},
pages = {180\textendash193},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {In today's highly competitive and interconnected global marketplace, the effective management of buyer-supplier relationships is essential for organizations seeking to stay ahead. With the rise of complex production facilities, ensuring product quality and optimizing communication between buyers and suppliers presents an escalating challenge. This complexity is further compounded by the integration of Digital Twins and Virtual Engineering, requiring innovative solutions to navigate the intricacies of modern supply chain dynamics. This article explores the role of Digital Twins and Virtual Engineering as a strategic approach to enhance buyer-supplier relationship management within the context of complex production facilities using insights from the Principal Agent Theory. Based on a systematic literature review, we explore current approaches to the use of virtual engineering and digital twins to overcome existing tensions from principal-agent theory.},
keywords = {Buyer-Supplier Relationship, Digital Twin, Production, Virtual Engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
In today's highly competitive and interconnected global marketplace, the effective management of buyer-supplier relationships is essential for organizations seeking to stay ahead. With the rise of complex production facilities, ensuring product quality and optimizing communication between buyers and suppliers presents an escalating challenge. This complexity is further compounded by the integration of Digital Twins and Virtual Engineering, requiring innovative solutions to navigate the intricacies of modern supply chain dynamics. This article explores the role of Digital Twins and Virtual Engineering as a strategic approach to enhance buyer-supplier relationship management within the context of complex production facilities using insights from the Principal Agent Theory. Based on a systematic literature review, we explore current approaches to the use of virtual engineering and digital twins to overcome existing tensions from principal-agent theory.