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One- and two-objective approaches to an area-constrained habitat reserve site selection problem

机译:区域受限的栖息地保护区选址问题的一目标和二目标方法

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We compare several ways to model a habitat reserve site selection problem in which an upper bound on the total area of the selected sites is included. The models are cast as optimization coverage models drawn from the location science literature. Classic covering problems typically include a constraint on the number of sites that can be selected. If potential reserve sites vary in terms of area, acquisition cost or land value, then sites need to be differentiated by these characteristics in the selection process. To address this within the optimization model, the constraint on the number of selected sites can either be replaced by one limiting the total area of the selected sites or area minimization can be incorporated as a second objective. We show that for our dataset and choice of optimization solver average solution time improves considerably when an area-constrained reserve site selection problem is modeled as a two objective rather than a single objective problem with a constraint limiting the total area of the selected sites. Computational experience is reported using a large dataset from Australia
机译:我们比较了几种建模栖息地保护区选择问题的方法,其中包括了所选保护区总面积的上限。这些模型被转换为从位置科学文献中得出的优化覆盖率模型。经典的覆盖问题通常包括对可以选择的站点数量的限制。如果潜在的保护区在面积,购置成本或土地价值方面有所不同,则在选择过程中需要通过这些特征来区分这些区。为了在优化模型中解决此问题,可以用限制所选站点总面积的一个替换所选站点数量的约束,或者可以将面积最小化作为第二个目标。我们表明,对于我们的数据集和优化求解器的选择,当将区域约束的储备站点选择问题建模为两个目标而非单个目标问题且约束条件限制了所选站点的总面积时,平均求解时间将大大缩短。使用来自澳大利亚的大型数据集报告了计算经验

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