Optimisation of Resource Allocation for Invasive Alien Species Surveillance Based on Bi-level Programming

Yitong Wang ()
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Yitong Wang: Nanjing University of Science and Technology

A chapter in Proceedings of the 2025 7th International Conference on Economic Management and Cultural Industry (ICEMCI 2025), 2025, pp 100-107 from Springer

Abstract: Abstract Surveillance of invasive alien species critically safeguards national biosecurity. Using Bursaphelenchus xylophilus as our case study, this paper address cross-regional transmission and infection uncertainty through a bi-level programming model for surveillance resource allocation. This enables efficient multi-level governmental deployment. The upper-level model aims to maximize the number of infested counties detected, enabling the superior government to delineate pest dispersal boundaries. The lower-level model seeks to maximize the number of infested sites detected within jurisdictions, assisting local governments in implementing refined surveillance of outbreaks. Multiple invasion probability scenarios are introduced to characterize the stochastic risk of the pest spread. An approximate linearization method is employed to transform the model into a mixed-integer programming formulation, so that it can be solved by using backward induction. Test results demonstrate that the bi-level programming model effectively expands the number of monitoring sites. It achieves risk-resource balance by dynamically adapting inter-tier allocation ratios in complex environments. Furthermore, the detection capacity of local governments directly shapes resource allocation between the two levels.

Keywords: Invasive alien species; Resource allocation; Bi-level programming; Bursaphelenchus xylophilus; Uncertainty (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-888-2_13

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DOI: 10.2991/978-94-6463-888-2_13

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