The problem attempted in this paper is to select a sample from a large set where the sample is required to have a particular average property. The problem can be expressed as an optimisation problem where one selects a subset of r objects from a group of n objects and the objective function is the mismatch between the required average property and that of a proposed sample. We test our method on a real-life problem which arises when we model the assets of a life insurance company in order to understand its risk, solvency and/or capital requirements.In this paper we describe a genetic algorithm developed to solve the generic selection task. We demonstrate the algorithm successfully solving our test problem.
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机译：本文试图解决的问题是从一大组样本中选择一个样本，在该样本中样本需要具有特定的平均属性。该问题可以表示为一个优化问题，即从一组 n 个对象中选择 r 个对象的子集，而目标函数是所需平均属性与拟议样本的数据。我们在对人寿保险公司的资产进行建模以了解其风险，偿付能力和/或资本要求时出现的现实问题中测试我们的方法。在本文中，我们描述了一种为解决通用选择而开发的遗传算法任务。我们演示了该算法成功解决了我们的测试问题。
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