期刊
IEEE CONTROL SYSTEMS LETTERS
卷 5, 期 2, 页码 547-552出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LCSYS.2020.3003401
关键词
Resource management; Mathematical model; Process control; Computational modeling; Programming; Sparse matrices; Upper bound; Compartmental and positive systems; control of networks; large-scale systems; optimization
资金
- Air Force Office of Scientific Research, Research and Development [FA2386-19-1-4076]
This study presents a method for sparse allocation of resources to control spreading processes using convex optimization, particularly exponential cone programming. By introducing a risk model to optimize the product of the likelihood and future impact of an outbreak, the method can provide more targeted resource allocation. Experimental results with a simplified wildfire example show the effectiveness of this approach compared to previous geometric programming methods.
In this letter we propose a method for sparse allocation of resources to control spreading processes - such as epidemics and wildfires - using convex optimization, in particular exponential cone programming. Sparsity of allocation has advantages in situations where resources cannot easily be distributed over a large area. In addition, we introduce a model of risk to optimize the product of the likelihood and the future impact of an outbreak. We demonstrate with a simplified wildfire example that our method can provide more targeted resource allocation compared to previous approaches based on geometric programming.
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