We consider the {\em vector partition problem}, where $n$ agents, each with a $d$-dimensional attribute vector, are to be partitioned into $p$ parts so as to minimize cost which is a given function on the sums of attribute vectors in each part. The problem has applications in a variety of areas including clustering, logistics and health care. We consider the complexity and parameterized complexity of the problem under various assumptions on the natural parameters $p,d,a,t$ of the problem where $a$ is the maximum absolute value of any attribute and $t$ is the number of agent types, and raise some of the many remaining open problems.

翻译：我们考虑到 ~ 矢量分布问题}, 美元代理物, 每一个都有美元维度属性矢量, 被分割成美元元件, 以最大限度地减少每一部分属性矢量总和上的一个特定函数的成本。 这个问题在多个领域都有应用, 包括集群、 物流和医疗保健。 我们考虑到问题的复杂性和参数的复杂性, 其依据是对自然参数的各种假设 $p, d, a, t$ 问题, 美元是任何属性的最大绝对值, 美元是所有属性的绝对值, 美元是各类属性的数量, 并提出了许多剩余未决问题中的一些问题 。