基于奖牌学习算法的团队成员分配问题  

The Team Member Allocation Problem Based on the Medalist Learning Algorithm

作　　者：何旺 何胜学[1] Wang He;Shengxue He(Business School,University of Shanghai for Science and Technology,Shanghai)

机构地区：[1]上海理工大学管理学院,上海

出　　处：《建模与仿真》2025年第2期593-607,共15页Modeling and Simulation

摘　　要：高效且和谐的团队是组织成功的关键因素之一。团队的目标不仅在于完成任务,更在于促进成员能力提升和团队可持续发展。如何组建一个个人利益和群体利益均衡的团队是一项难题,因为这涉及到公平性问题。本文将团队组建视为一个多目标离散问题,并提出了一个综合考虑任务完成度、个人提升和群体公平性的优化模型。该模型旨在确保团队在尽可能保证达到任务目标的前提下,实现团队成员个人能力提升和同级成员间公平发展的均衡。通过对六个数据集进行优化求解,研究得出了最佳团队分配方案。对于一个以任务为导向的团队而言,团队规模在3到6人之间是最具效益的。这种规模的团队构成灵活多样,能够在完成任务的同时提供更多提升可能性。Efficient and harmonious teams are crucial for organizational success.The goals of a team extend beyond task completion to include the enhancement of members’abilities and the sustainable development of the team.Forming a team that balances individual and collective interests is a challenge due to fairness considerations.This paper views team formation as a multi-objective discrete problem and proposes an optimization model that comprehensively considers task completion,personal improvement,and group fairness.The model aims to ensure that,while meeting task objectives,there is a balance between the personal development of team members and fairness among peers.Through optimization across six datasets,the study derives optimal team allocation strategies.For task-oriented teams,a team size of 3 to 6 members is found to be the most beneficial.This team size offers flexibility and variety,enabling task completion while providing ample opportunities for individual growth.

关 键 词：团队构建 合作学习 团队公平 多目标离散优化 启发式算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]