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：本文尝试的问题是选择从一个大型集合的样本，其中需要特定的平均属性。问题可以表示为优化问题，其中一个人从一组 n 对象中选择 r 对象的子集，目标函数是所需的普通属性之间的不匹配提出的样本。我们在现实生活中测试我们的方法，当我们建模人寿保险公司的资产时出现的现实问题，以了解其风险，偿付能力和/或资本要求。本文介绍了开发的遗传算法，用于解决通用选择任务。我们展示了成功解决了我们的测试问题的算法。
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