Research On Net Present Value Optimization Of Distributed Multi-Project Scheduling Under Resource Constraints

In the distributed multi-project management scenario,more and more enterprises are faced with the risks caused by the increase in the number of projects,the expansion of project scale and the shortage of resource.Therefore,how to coordinate the allocation of multiproject resources and coordinate and optimize the schedule arrangement of multi-project is one of the urgent problems concerning multi-project schedule and resource management.The implementation of distributed resource-constrained multi-project scheduling not only requires independent scheduling of each project,but also coordination of limited shared resources.Therefore,Considering the complexity of multi-project environment,this paper takes distributed resource constrained multi-project scheduling problem as the research object,and optimizes the multi-project schedule through reasonable allocation of local resources(only used within the project)and global resources(shared among projects),so as to achieve the goal of maximizing the benefits of multiple projects.The main research work of this paper is as follows:First,under the rigid constraint of global resources,considering the finiteness of rigid resources,the greedy selection strategy is adopted to determine the activity arrangement at the moment when global resource conflicts occur,and the integer programming model aiming at the maximum net present value is constructed for it,meanwhile the genetic algorithm is used to solve the model.Based on 60 cases in the MPSPLIB,the algorithm test and sensitivity analysis of key parameters are carried out.It is proved that using greedy choice strategy to coordinate activity arrangement can effectively improve the net present value of the projectSecondly,considering the fact that resources can be obtained from the market through leasing,purchasing and other means in reality,the rigid constraint of global resources is extended to the flexible constraint.In case of global resource conflicts,resources can be obtained from outside to solve the problem of resource shortage.Building a distributed multi-project scheduling optimization model based on a fixed time scale of resource procurement,and designs a hybrid genetic-tabu search algorithm to solve the problem.Also the numerical experiment was carried out based on the MPSPLIB,and the sensitivity analysis of the key parameters was carried out to verify the effectiveness of the algorithm and the feasibility of the method,then prove that the procurement of global resources within the time scale can effectively improve the performance objectives of multiple projects.Finally,a practical case is applied to the problem studied in this paper,which is substituted into the maximum net present value optimization model of distributed multiproject scheduling with rigid resource constraints and the maximum net present value optimization model of distributed multi-project scheduling with flexible resource constraints,and the corresponding meta-heuristic algorithm is used to solve the problem,then the scheduling results under the two schemes are compared and analyzed.The experimental results show that although obtaining resources from outside will increase the project cost,compared with the traditional rigid constraints of global resources,purchasing global flexible resources on a time scale can significantly improve the revenue performance of distributed multi-projects.The research results of this paper can help enterprises avoid project risks in advance,reduce the adverse impact on the overall project schedule and economic benefits,so as to effectively improve the distributed multi-project performance objectives,which can provide decision-making basis for the establishment of reasonable schedule plans for distributed multi-project in practice,which has important practical significance.