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A decomposition solution approach to the troops-to-tasks assignment in military peacekeeping operations

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  • Nadia Chaudry
  • Ingunn Vermedal
  • Kjetil Fagerholt
  • Maria Fleischer Fauske
  • Magnus StÃ¥lhane

Abstract

This paper considers the Peacekeeping Troops-to-Tasks Problem (PTTP). The PTTP deals with assigning battlegroup resources to a set of tasks associated with a given peacekeeping mission. The tasks may be spread across several locations, and have requirements regarding the time at which they can be handled, and the skills and skill levels needed to complete them. There is also a utility value related to each completed task that reflects its importance. The resources are bound by a hierarchy of command, limiting their movement in relation to one another. The aim is to decide which tasks to complete, when, and by whom. We present a mathematical compact model for the PTTP, which includes a number of complicating real-life factors. Due to the complexity of the compact model, it is difficult to solve large instances using a commercial solver. Therefore, we also propose a decomposition-based solution approach, with a decomposed model where possible travel routes for the resources are generated a priori. The computational study shows that the decomposed model has better performance than the compact model, and that it can be used as a good starting point for developing a useful decision support tool for military peacekeeping operations planning.

Suggested Citation

  • Nadia Chaudry & Ingunn Vermedal & Kjetil Fagerholt & Maria Fleischer Fauske & Magnus StÃ¥lhane, 2020. "A decomposition solution approach to the troops-to-tasks assignment in military peacekeeping operations," The Journal of Defense Modeling and Simulation, , vol. 17(4), pages 357-371, October.
    • Handle: RePEc:sae:joudef:v:17:y:2020:i:4:p:357-371
    DOI: 10.1177/1548512919875230
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    1. Ranjbar, Mohammad & De Reyck, Bert & Kianfar, Fereydoon, 2009. "A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling," European Journal of Operational Research, Elsevier, vol. 193(1), pages 35-48, February.
    2. Hartmann, Sönke & Briskorn, Dirk, 2010. "A survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 207(1), pages 1-14, November.
    3. George B. Dantzig & Philip Wolfe, 1960. "Decomposition Principle for Linear Programs," Operations Research, INFORMS, vol. 8(1), pages 101-111, February.
    4. Stefan Irnich & Guy Desaulniers, 2005. "Shortest Path Problems with Resource Constraints," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 33-65, Springer.
    5. Lam T. Bui & Michael Barlow & Hussein A. Abbass, 2009. "A Multi-Objective Risk-Based Framework For Mission Capability Planning," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 459-485.
    6. D. Debels & M. Vanhoucke, 2005. "A Decomposition-Based Heuristic For The Resource-Constrained Project Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/293, Ghent University, Faculty of Economics and Business Administration.
    7. Drexl, Andreas & Nissen, Rudiger & Patterson, James H. & Salewski, Frank, 2000. "ProGen/[pi]x - An instance generator for resource-constrained project scheduling problems with partially renewable resources and further extensions," European Journal of Operational Research, Elsevier, vol. 125(1), pages 59-72, August.
    8. Peteghem, Vincent Van & Vanhoucke, Mario, 2010. "A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 201(2), pages 409-418, March.
    9. Bianco, L. & Dell'Olmo, P. & Grazia Speranza, M., 1998. "Heuristics for multimode scheduling problems with dedicated resources," European Journal of Operational Research, Elsevier, vol. 107(2), pages 260-271, June.
    10. Dieter Debels & Mario Vanhoucke, 2007. "A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem," Operations Research, INFORMS, vol. 55(3), pages 457-469, June.
    11. A Sprecher, 2002. "Network decomposition techniques for resource-constrained project scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 405-414, April.
    12. Adhau, Sunil & Mittal, M.L. & Mittal, Abhinav, 2013. "A multi-agent system for decentralized multi-project scheduling with resource transfers," International Journal of Production Economics, Elsevier, vol. 146(2), pages 646-661.
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