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Addressing Problem Drift in UNHCR Fund Allocation

Authors Sameela Suharshani Wijesundara , Maria Garcia de la Banda , Guido Tack

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Sameela Suharshani Wijesundara
  • Department of Data Science and AI, Faculty of IT, Monash University, Clayton, Australia
  • ARC Industrial Training and Transformation Centre OPTIMA, Clayton, Australia
Maria Garcia de la Banda
  • Department of Data Science and AI, Faculty of IT, Monash University, Clayton, Australia
  • ARC Industrial Training and Transformation Centre OPTIMA, Clayton, Australia
Guido Tack
  • Department of Data Science and AI, Faculty of IT, Monash University, Clayton, Australia
  • ARC Industrial Training and Transformation Centre OPTIMA, Clayton, Australia

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Sameela Suharshani Wijesundara, Maria Garcia de la Banda, and Guido Tack. Addressing Problem Drift in UNHCR Fund Allocation. In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 37:1-37:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.CP.2023.37

Abstract

Optimisation models are concise mathematical representations of real-world problems, usually developed by modelling experts in consultation with domain experts. Typically, domain experts are only indirectly involved in the problem modelling process, providing information and feedback, and thus perceive the deployed model as a black box. Unfortunately, real-world problems "drift" over time, where changes in the input data parameters and/or requirements cause the developed model to fail. This requires modelling experts to revisit and update deployed models. This paper identifies the issue of problem drift in optimisation problems using as case study a model we developed for the United Nations High Commissioner for Refugees (UNHCR) to help them allocate funds to different crises. We describe the initial model and the challenges due to problem drift that occurred over the following years. We then use this case study to explore techniques for mitigating problem drift by including domain experts in the modelling process via techniques such as domain specific languages.

Subject Classification

ACM Subject Classification
  • Theory of computation → Constraint and logic programming
  • Software and its engineering → Constraint and logic languages
Keywords
  • Fund Allocation
  • Problem Drift
  • Domain Specific Languages
  • MiniZinc

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References

  1. A. Biere, M. Heule, and H. van Maaren. Handbook of Satisfiability. IOS Press, January 2009. Google Scholar
  2. Grady Booch, James E. Rumbaugh, and Ivar Jacobson. The unified modeling language user guide - covers UML 2.0, Second Edition. Addison Wesley object technology series. Addison-Wesley, 2005. Google Scholar
  3. Peter P. Chen. The entity-relationship model - toward a unified view of data. ACM Trans. Database Syst., 1(1):9-36, 1976. URL: https://doi.org/10.1145/320434.320440.
  4. Sebastian Erdweg, Tijs van der Storm, Markus Völter, Meinte Boersma, Remi Bosman, William R. Cook, Albert Gerritsen, Angelo Hulshout, Steven Kelly, Alex Loh, Gabriël D. P. Konat, Pedro J. Molina, Martin Palatnik, Risto Pohjonen, Eugen Schindler, Klemens Schindler, Riccardo Solmi, Vlad A. Vergu, Eelco Visser, Kevin van der Vlist, Guido H. Wachsmuth, and Jimi van der Woning. The State of the Art in Language Workbenches. In David Hutchison, Takeo Kanade, Josef Kittler, Jon M. Kleinberg, Friedemann Mattern, John C. Mitchell, Moni Naor, Oscar Nierstrasz, C. Pandu Rangan, Bernhard Steffen, Madhu Sudan, Demetri Terzopoulos, Doug Tygar, Moshe Y. Vardi, Gerhard Weikum, Martin Erwig, Richard F. Paige, and Eric Van Wyk, editors, Software Language Engineering, volume 8225, pages 197-217. Springer International Publishing, Cham, 2013. Series Title: Lecture Notes in Computer Science. URL: https://doi.org/10.1007/978-3-319-02654-1_11.
  5. Robert Fourer, David M Gay, and Brian W Kernighan. A modeling language for mathematical programming. Management Science, 36(5):519-554, 1990. Google Scholar
  6. Martin Fowler. Domain-Specific Languages. Pearson Education, September 2010. Google Scholar
  7. Alan M. Frisch, Warwick Harvey, Chris Jefferson, Bernadette Martínez-Hernández, and Ian Miguel. Essence: A constraint language for specifying combinatorial problems. Constraints, 13(3):268-306, September 2008. URL: https://doi.org/10.1007/s10601-008-9047-y.
  8. Paul Hudak. Domain Specific Languages. Handbook of programming languages, 3(39-60):23, 1997. Google Scholar
  9. Youn-ah Kang and John Stasko. Examining the Use of a Visual Analytics System for Sensemaking Tasks: Case Studies with Domain Experts. IEEE Transactions on Visualization and Computer Graphics, 18(12):2869-2878, December 2012. URL: https://doi.org/10.1109/TVCG.2012.224.
  10. Jie Liu, Tim Dwyer, Kim Marriott, Jeremy Millar, and Annette Haworth. Understanding the Relationship Between Interactive Optimisation and Visual Analytics in the Context of Prostate Brachytherapy. IEEE Transactions on Visualization and Computer Graphics, 24(1):319-329, January 2018. URL: https://doi.org/10.1109/TVCG.2017.2744418.
  11. Jie Liu, Tim Dwyer, Guido Tack, Samuel Gratzl, and Kim Marriott. Supporting the Problem-Solving Loop: Designing Highly Interactive Optimisation Systems. IEEE Transactions on Visualization and Computer Graphics, 27(2):1764-1774, February 2021. URL: https://doi.org/10.1109/TVCG.2020.3030364.
  12. David Meignan, Sigrid Knust, Jean-Marc Frayret, Gilles Pesant, and Nicolas Gaud. A Review and Taxonomy of Interactive Optimization Methods in Operations Research. ACM Transactions on Interactive Intelligent Systems, 5(3):1-43, October 2015. URL: https://doi.org/10.1145/2808234.
  13. Marjan Mernik, Jan Heering, and Anthony M Sloane. When and how to develop domain-specific languages. ACM computing surveys (CSUR), 37(4):316-344, 2005. Google Scholar
  14. Nicholas Nethercote, Peter J. Stuckey, Ralph Becket, Sebastian Brand, Gregory J. Duck, and Guido Tack. MiniZinc: Towards a Standard CP Modelling Language. In Christian Bessière, editor, Principles and Practice of Constraint Programming – CP 2007, Lecture Notes in Computer Science, pages 529-543, Berlin, Heidelberg, 2007. Springer. URL: https://doi.org/10.1007/978-3-540-74970-7_38.
  15. Václav Pech. JetBrains MPS: Why Modern Language Workbenches Matter. In Antonio Bucchiarone, Antonio Cicchetti, Federico Ciccozzi, and Alfonso Pierantonio, editors, Domain-Specific Languages in Practice: with JetBrains MPS, pages 1-22. Springer International Publishing, Cham, 2021. URL: https://doi.org/10.1007/978-3-030-73758-0_1.
  16. P. Pirolli and S. Card. The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In Proceedings of international conference on intelligence analysis, volume 5. McLean, VA, USA, 2005. Google Scholar
  17. Francesca Rossi, Peter van Beek, and Toby Walsh. Handbook of Constraint Programming. Elsevier, August 2006. Google Scholar
  18. UNHCR Global Appeal 2023. Accessed on 5 May, 2023. URL: https://reporting.unhcr.org/globalappeal2023.
  19. UNHCR Global Report 2022. Accessed on 5 May, 2023. URL: https://reporting.unhcr.org/global-report-2022.
  20. UNHCR operations plan in emergencies. Accessed on 5 May, 2023. URL: https://emergency.unhcr.org/support-response/planning-and-programming/unhcr-operations-plan-emergencies.
  21. Arie van Deursen, Paul Klint, and Joost Visser. Domain-specific languages: an annotated bibliography. ACM SIGPLAN Notices, 35(6):26-36, June 2000. URL: https://doi.org/10.1145/352029.352035.
  22. Pascal Van Hentenryck. The OPL optimization programming language. MIT Press, Cambridge, MA, USA, 1999. Google Scholar
  23. Laurence A. Wolsey. Integer Programming. John Wiley & Sons, September 2020. Google Scholar
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