We consider the following problem in which a given number of items has to be chosen from a predefined set. Each item is described by a vector of attributes and for each attribute there is a desired distribution that the selected set should have. We look for a set that fits as much as possible the desired distributions on all attributes. Examples of applications include choosing members of a representative committee, where candidates are described by attributes such as sex, age and profession, and where we look for a committee that for each attribute offers a certain representation, i.e., a single committee that contains a certain number of young and old people, certain number of men and women, certain number of people with different professions, etc. With a single attribute the problem collapses to the apportionment problem for party-list proportional representation systems (in such case the value of the single attribute would be a political affiliation of a candidate). We study the properties of the associated subset selection rules, as well as their computation complexity.
翻译:我们考虑了从预定的一组中选择一定数量的项目的下列问题:每个项目都必须从预定的一组中选择,每个项目都由一个属性矢量来描述,每个属性都有所希望的分布。我们寻找一套尽可能符合所有属性所需分布的集合。申请的例子包括选择一个代表委员会成员,其中候选人按性别、年龄和职业等属性来描述,以及我们寻找一个对每个属性提供一定代表性的委员会,即一个包含一定数量的年轻人和老年人、某些男女、某些不同专业的人等的单一委员会。我们仅将问题归结于政党名单比例代表制的分配问题(在这种情况下,单一属性的价值将是候选人的政治归属)。我们研究相关的子集选择规则的特性及其计算复杂性。