A Study On Multi-mode Resource Constrained Project Scheduling Problem Based On Ant Colony Algorithm

Since the 50s of last century, project management theory has been applied very widely with the socio-economic development: the areas of studying expanding, the depth of their research increasing. Now, as the world economy develops and the co-operation led by the economic globalization deepens, the project management is considered more and more important by the enterprises. How to make a program be completed on schedule under resource constrained by make reasonable arrangements for the various activities has become an issues of common concern for majorities of the enterprises. It is said that RCPSP has been studying by more and more scholars As the economy develops, uncertainty of enterprises led by environment increases. Project managers often need make a flexible and effective plan for the allocation of resources between the activities of the program to achieve the established objectives of project management. Therefore, it is very important to achieve the best balance between the cost and time under uncertain project environment. However, the domestic research on RCPSP is mostly based on the assumption that one activity should be finished in one mode with fixed duration, Research on MRCPSP is still very little. Therefore, we study the MRCPSP that refers to the multi-mode activity to instruct the practice.Firstly, on the basis that defining the characteristics of MRCPSP and review the mathematical models for RCPSP, we construct the mathematical model for MRCPSP under the condition that one activity has at least one execution mode and each mode corresponds to one duration. In order to solve above model, we emphatically discussed the basic principle of the swarm intelligence algorithm—the Ant Colony Algorithm as well as improvement research for current algorithm, and then proposed a new improved Ant Colony Algorithm and analyses its application process in the multi-mode resource-constrained project scheduling problem; Lastly, in order to confirm the validity of the model and the algorithm, we take an experiment based on the standard instances of PSLIB. The experimental result indicated that the model and the algorithm proposed in this dissertation are both efficient and effective.This research not only burdens the research field of resources constrained project scheduling problem, but also makes certain guidance for achieving the balance between cost and time in the process of program management. On the other hands, the application of the Ant Colony Algorithm in MRCPSP, which always used in other optimization problems, provides some important train of thought and method for resources constrained project scheduling problem, what's more, widens the application area of Ant Colony optimization algorithm.