Online voluntary mentoring: Optimising the assignment of students and mentors
本文研究了疫情期间匈牙利一个非政府组织项目中的优化问题，通过整数规划技术将志愿导师与学生进行最优匹配，并基于真实和模拟数据评估了动态匹配方案的表现。
After the closure of the schools in Hungary from March 2020 due to the pandemic, many students were left at home with no or not enough parental help for studying, and in the meantime some people had more free time and willingness to help others in need during the lockdown. In this paper we describe the optimisation aspects of a joint NGO project for allocating voluntary mentors to students using a web-based coordination mechanism. The goal of the project has been to form optimal pairs and study groups by taking into account the preferences and the constraints of the participants. In this paper, we present the optimisation concept and the integer programming techniques used for solving the allocation problems. Furthermore, we conducted computational simulations on real and generated data to evaluate the performance of this dynamic matching scheme under different parameter settings.