减少随机数在学校录取匹配算法中的作用
Reducing the role of random numbers in matching algorithms for school admission
摘要：
提出了解决大学入学问题的新方法，并在各种简单的情况下用蒙特卡洛模拟。基于一个限定符定义为平均排名，它被发现，这些方法是更有效的比波士顿和延期接受算法。效率的提高与随机决胜局的作用减少直接相关。新方法的防策略性也进行了评估。
英文摘要：
New methods for solving the college admissions problem with indifference are presented and characterised with a Monte Carlo simulation in a variety of simple scenarios. Based on a qualifier defined as the average rank, it is found that these methods are more efficient than the Boston and Deferred Acceptance algorithms. The improvement in efficiency is directly related to the reduced role of random tie-breakers. The strategy-proofness of the new methods is assessed as well.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
