Research On Decision Methods Considering Colleagues Preferences For Project-employee Matching

As the operation of enterprises tends to project management,the matching of employees in the project team has been drawn increasing attention.A reasonable project-employee matching not only keeps the employee in a good working condition,but also improves the efficiency and effectiveness of the project team.In recent years,project-employee matching problem has been widely studied by scholars both at home and abroad,and achieved some achievements.However,there are some limitations that have not been solved yet.For example,group or colleagues preference relations between group members have great influence on the degree of the cooperation between members and the efficiency and quality of the project team,however,it is seldom discussed.Due to the complexity of the real problems,it is difficult for matching agents to give exact preference ordering,there will be incomplete,uncertain and weak preference types of information.Therefore,how to deal with different types of matching information is still to be further studied.As the scale of the matching problem increasing,the current solutions can not quickly find the satisfactory matching results.To overcome these limitations,evidential reasoning and ant colony algorithm are used to deal with the project-employee matching problems,which not only considers colleagues preferences but also deals with the incomplete,uncertain or weak preference information,and gives the corresponding solving method.This thesis consists of the following three aspects:(1)To solve project-employee matching decision problem with complete preference ordering information,a decision making method considering colleagues preferences is proposed.Firstly,according to the weak preference ordering information provided by projects and employees,the employees' satisfaction degrees at projects,the projects' satisfaction degrees at employees and the employees' satisfaction degrees at the other employees are calculated.Secondly,a multi-objective matching decision model considering colleagues preferences which maximizes the satisfaction degrees of the matching is constructed and solved.(2)To solve project-employee matching decision problem with incomplete preference ordering information,a decision making method considering colleagues preferences is proposed.Firstly,the incomplete ordering information provided by matching agents is transformed into rank belief degrees.Secondly,the normalized matching information is taken as pieces of evidence,the fusion satisfaction degrees of project-employee and employee-other employees are aggregated by using the evidential reasoning approach.Finally,a two-sided matching decision model considering colleagues preferences which maximizes the fusion satisfaction degrees is constructed and solved.(3)To solve project-employee matching problem considering colleagues preferences quickly,according to the characteristics of the matching model,a solving method is proposed in this thesis by improving ant colony algorithm.Firstly,the projects and employees are regarded as the point of the TSP(Traveling Salesman Problem)figure(the city of TSP problem).Secondly,the distance formula between the points and distance updating formula,and the ant pheromone updating formula are constructed.Finally,it is quickly to get the optimal matching results after many iterations.