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数学规划在遗传生物防治中的应用

APPLICATIONS OF MATHEMATICAL PROGRAMMING TO GENETIC BIOCONTROL.

作者信息

Vásquez Váleri N, Marshall John M

机构信息

Energy and Resources Group, Rausser College of Natural Resources, University of California Berkeley, Berkeley, CA 94705 USA.

Division of Epidemiology and Biostatistics, School of Public Health, University of California Berkeley, Berkeley, CA 94704 USA.

出版信息

SIAM J Appl Math. 2024;84(3):S392-S411. doi: 10.1137/22m1509862.

Abstract

We review existing approaches to optimizing the deployment of genetic biocontrol technologies-tools used to prevent vector-borne diseases such as malaria and dengue-and formulate a mathematical program that enables the incorporation of crucial ecological and logistical details. The model is comprised of equality constraints grounded in discretized dynamic population equations, inequality constraints representative of operational limitations including resource restrictions, and an objective function that jointly minimizes the count of competent mosquito vectors and the number of transgenic organisms released to mitigate them over a specified time period. We explore how nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP) can advance the state of the art in designing the operational implementation of three distinct transgenic public health interventions, two of which are presently in active use around the world.

摘要

我们回顾了现有的优化基因生物防治技术部署的方法,这些技术是用于预防疟疾和登革热等媒介传播疾病的工具,并制定了一个数学程序,该程序能够纳入关键的生态和后勤细节。该模型由基于离散动态种群方程的等式约束、代表包括资源限制在内的操作限制的不等式约束以及一个目标函数组成,该目标函数在特定时间段内联合最小化有能力的蚊媒数量以及为减轻蚊媒数量而释放的转基因生物数量。我们探讨了非线性规划(NLP)和混合整数非线性规划(MINLP)如何在设计三种不同的转基因公共卫生干预措施的操作实施方面推动技术发展,其中两种目前正在全球积极使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4ee/11741675/21e2f9b996dd/nihms-2008113-f0001.jpg

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