Abstract: A decision-making method is proposed to solve the two-sided matching problem between personnel and positions considering collaborative information. Firstly, the description of two-sided matching problem between personnel and positions considering collaborative information is given. Then, the personnel satisfaction with positions, the positions satisfaction with individual skills of personnel and collaborative degree among personnel are computed based on the multi-criteria evaluation information given by personnel and positions. And on this basis a multi-objective optimization model is built to maximize the personnel satisfaction, positions satisfaction with individual skills of personnel and the collaborative degree among personnel. Furthermore, given that the model is a 0-1 quadratic integral programming of multi-objective problem and is also a NP-hard problem, a multi-objective discrete differential evolution algorithm is developed to solve it. Finally, a numerical example illustrates the feasibility and validity of the proposed method.

Key words: two-sided matching, collaborative information, satisfaction, multi-objective optimization model, discrete differential evolution algorithm

摘要： 针对考虑协同信息的人员与岗位双边匹配问题,提出一种决策分析方法。首先,给出了考虑协同信息的人员与岗位双边匹配问题描述;其次,依据人员和岗位给出的多指标评价信息,计算了人员对岗位的满意度、岗位对人员的个体技能满意度及人员之间的工作协同度;在此基础上,建立了以人员对岗位满意度最大、岗位对人员个体技能满意度最大和人员之间协同度最大为目标的多目标优化模型,该模型是一个具有多目标的0-1型二次整数规划问题,也是一个NP-hard问题,为了求解该多目标优化模型,设计了一个多目标离散差分进化算法;最后,通过一个实例验证了所提方法的可行性和有效性。

关键词: 双边匹配, 协同信息, 满意度, 多目标优化模型, 离散差分进化算法