We focus on an online 2-stage problem, motivated by the following situation: consider a system where students shall be assigned to universities. There is a first round where some students apply, and a first (stable) matching $M_1$ has to be computed. However, some students may decide to leave the system (change their plan, go to a foreign university, or to some institution not in the system). Then, in a second round (after these deletions), we shall compute a second (final) stable matching $M_2$. As it is undesirable to change assignments, the goal is to minimize the number of divorces/modifications between the two stable matchings $M_1$ and $M_2$. Then, how should we choose $M_1$ and $M_2$? We show that there is an {\it optimal online} algorithm to solve this problem. In particular, thanks to a dominance property, we show that we can optimally compute $M_1$ without knowing the students that will leave the system. We generalize the result to some other possible modifications in the input (students, open positions). We also tackle the case of more stages, showing that no competitive (online) algorithm can be achieved for the considered problem as soon as there are 3 stages.
翻译:我们集中关注一个在线的2阶段问题,其动机是以下情形:考虑一个将学生分配到大学的系统。有的是第一轮,一些学生可以申请,而第一个(稳定)符合1美元。然而,有些学生可以决定离开系统(改变计划,去外国大学,或者去系统以外的机构)。然后,在第二轮(这些删除之后),我们将计算出第二个(最终)稳定地相当于$M_2美元。由于改变任务是不可取的,目标是尽量减少两个稳定匹配的M_1美元和$2美元之间的离婚/修改数量。然后,我们应该如何选择$1美元和$2美元?我们显示有一个解决该问题的最佳的在线算法。特别是由于占优势的财产,我们证明我们可以最佳地计算$M_1美元,而不会知道离开系统的学生。我们的目标是将结果概括为在两个稳定匹配的$M_1美元和$2美元之间的其他可能的修改(测试结果,开放的状态),我们也可以很快将结果推广到其他输入(测试,开放的状态)中去掉三个阶段。我们还考虑过竞争阶段。