Research On Multi-objective Project Planning And Scheduling Model Based On Multi-skill Human Resources

In the construction industry,construction machinery,raw materials and human resources are the main factors that affect the completion cycle of the project.When construction machinery is certain,human resources become the key resources that can be optimized to affect the efficiency of the project.In the case of limited human resources and lack of multi-skilled workers,enterprises and organizations also pay more and more attention to human resource cost control and personnel scheduling.Human resources within project groups tend to have multiple skills and different human resources use different skills with different efficiencies,but managers are in the process human resources scheduling only takes into account their most efficient skills,the use of human resources is inefficient.Therefore,it is of great practical significance to study the problem of multi-objective project planning and scheduling based on multi-skilled human resources.Based on project scheduling and human resource management in engineering construction industry,this paper puts forward the multi-skill multi-objective project scheduling problem based on the difference of skill work efficiency,and studies three aspects of human resource limited project scheduling problem on this basis:1)dispatching of skilled workers with skills of varying efficiency,2)forecasting of workers’ work efficiency,3)allowing task outsourcing,the corresponding models are established for different problems,the simulation solution analysis is carried out,and the optimization results are compared.1.A multi-objective project planning and scheduling model based on multi-skilled human resources was established to allow workers to participate in construction with different skills with different work efficiency.Considering that workers use various skills with different working efficiency to participate in the planning and scheduling of construction,a multi-objective project planning and scheduling model based on multi-skilled human resources is constructed,which aims at project duration and human resource cost.The model incorporates staff within the project team and all the skills they possess into the search space,in contrast to the traditional single-skill scheduling of workers.The results show that allowing workers to use multiple skills to participate in construction can effectively improve the utilization rate of human resources and shorten the construction period.2.Aiming at the problem of improving the working efficiency of skilled workers,the paper introduces learning curve to predict the working efficiency of workers,so that the project duration solved is closer to reality,and establishes a multi-skilled workers multi-objective project planning and scheduling model considering the increase of skill proficiency.The multi-objective project planning and scheduling model for workers with project duration,human resource cost and skill value improvement as the optimization target is constructed.The results of simulation show that,in the course of the project,taking into account the improvement of the working efficiency of the workers,and assigning workers to the workers involved in the project based on the improved proficiency,can increase the income of the workers and arouse their enthusiasm;it can help to train general practitioners and improve the adaptability of enterprises.3.Task outsourcing can balance resources on a larger scale and thus improve resource utilization.A multi-objective project planning and scheduling model based on task-splitable outsourcing considering skilled workers is established to allow task outsourcing and collaboration tasks to be split arbitrarily.Aiming at the continuous optimization problem which can be split arbitrarily,the multi-objective differential evolution algorithm is used to deal with the better characteristics of the continuous change problem,and the multi-objective differential evolution algorithm is combined with the improved non-dominated fast ranking genetic algorithm to solve the problem.