Integrated Management Of Project Resources Based On Schedule Optimization

In traditional resource constraint project schedule problem, contractors only range project schedule according to their self-owned resources. The literatures about the RIP and the RRP commonly assume that the contractors have no any resources which are needed to perform the activities and rent or buy resources to fulfill the project. In actual commercial operation, the contractors often have self-owned resources. Limited to their resource capacity, they may buy resources or hire from the outside, or even outsourcing some work to shorten the project cycle and increase the project income. For many real-life projects, however, the contractors only rent bottleneck resources other than their self-owned resources, and the clients often set up a bonus/penalty structure to lateness from the due date of the project to encourage the contractors to fulfill the project on time and save cost.In this paper, we assume that the resources used to perform the activities can be self-owned or rented, and there is a bonus/penalty per lateness from the due date of the project. We finally build a resource integration model which is more valuable on practical application. The resource integration model assumes that the contractors have some self-owned resources and allows that the contractors can get outside resources by paying additional costs. The clients set up due date and bonus/penalty structure while the contractors try to minimize their total cost by scheduling according to resources and due date. In this paper, we modify the preprocess method of redundant modes usually used in multi-mode resource constraint project scheduling problem, and develop a modes deleting algorithm which is fit for the RIM problem. According to test results, the modes deleting algorithm can significantly reduce the complexity of the problem. After analyzing the resource integration model, we develop a genetic algorithm by two coding ways of schedule coding and order coding, and embed a local search algorithm which called flexible critical chain compressing in order to improve the whole performance. Instance test shows that the genetic algorithm by schedule coding is more efficient and the flexible critical chain compressing algorithm is efficient for the problem. The results reveal that the resource integration model can improve the revenue of the project and is more practice than the resource constraint project scheduling problem.Here are the innovation points of this paper. At first we consider the internal resources and external resources integrated and release the deadline limit, those make the RIM be more practical for the project management than classical theory. Then we propose a suitable pretreatment for the problem to delete redundant modes, and substantially reduced the complexity of the problem. Third, we attempt coding genes based on poset theory. Finally we design a flexible critical chain compression algorithm, speed up the convergence rate of the algorithm, and obtain good results.