# Quantum Computing Approaches for Mission Covering Optimization
## 7 Future Work  
Adding further capabilities to different resources in Scenario 2 would make for a more interesting/realistic optimization problems for quantum computers to solve. This is just one of the many alterations that can be applied to MCO to increase the complexity of the optimization problem.  
In this paper, resource dependencies are modeled within MCO; however, there may be missions with different priorities along with mission dependencies. Furthermore, in this work, resources were only shown to possess one type of qualification. However, there can be cases where a resource may have many types of qualifications. At the heart of MCO, it is an optimization problem concerning the allocation of resources invariant to time. An interesting direction for future study is how well this type of optimization problem can be ported to an extension of a job-shop problem.  
Although error mitigation is not a focus of this study, research for mitigating errors for QAOA is being conducted by others [22]. Employing error mitigation techniques for MCO is a direction of study.  
There are alternate techniques that can be employed on gate-based machines to solve QUBO problems. For example, the Grover adaptive search [23] is an iterative Grover-like approach that filters states based on a conditional oracle. Furthermore, filtering-VQE [24] can be used to solve optimization problems, utilizing filtering operators to achieve faster and more reliable convergence to the optimal solution.  
Lastly, another interesting solution method might entail the use of a 'bang-bang' strategy [25] for multiple constraints. Here, for each constraint \(C_{i}\) associated with a constraint Hamiltonian \(H_{i}\), one might randomly cycle through applications of individual \(H_{i}\) for each time step, as opposed to the application of the joint Hamiltonian \(H=\sum_{i}H_{i}\). While each \(H_{i}\) only preserves constraints \(C_{i}\), the supposition is that the application of \(H_{i}\) might only partially violate constraints \(C_{j\
eq i}\), if applied for a short time and randomly. This solution approach to MCO-like problems will be investigated in future work.  
Conceptualization and methodology, all authors contributed; software, M.C., A.G. and A.S.; resources, supervision and funding A.G., P.M.A. and L.W.; writing--review and editing, M.C., A.G. and P.M.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Data Availability Statement:** For any request related to the data please contact the corresponding author.  
**Acknowledgments:** The authors would like to thank [PERSON] and the exponential campaign at GE Research for supporting this effort, and [PERSON] and [PERSON] for useful discussions. The views expressed are those of the authors and do not reflect the official guidance or position of the United States Government, the Department of Defense, the United States Air Force or General Electric. The appearance of external hyperlinks does not constitute endorsement by the United States Department of Defense or General Electric of the linked websites, or the information, products, or services contained therein. The Department of Defense and General Electric do not exercise any editorial, security, or other control over the information you may find at these locations.  
**Conflicts of Interest:** The authors declare no conflict of interest.