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

Author:

Chaudry Nadia1,Vermedal Ingunn1,Fagerholt Kjetil1,Fauske Maria Fleischer2ORCID,Stålhane Magnus1

Affiliation:

1. Norwegian University of Science and Technology (NTNU), Norway

2. Norwegian Defence Research Establishment (FFI), Norway

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.

Publisher

SAGE Publications

Subject

Engineering (miscellaneous),Modeling and Simulation

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Troop to Task Optimization: Algorithmic Scheduling for USMC;2024 Systems and Information Engineering Design Symposium (SIEDS);2024-05-03

2. Two-stage stochastic programming model of US Army aviation allocation of utility helicopters to task forces;The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology;2023-11-18

3. A review of the role of heuristics in stochastic optimisation: from metaheuristics to learnheuristics;Annals of Operations Research;2021-06-08

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