Application Of Ant Colony Optimization In IT Project Schedule

As a new subject, research on project management has received more and more attentions nowadays. This thesis deals with the problems of resource optimization in IT project management when making project schedules, and tries to use Ant Colony Optimization, which is one of the popular algorithms on solving those problems currently, to get project plans and available resources more reasonably.The thesis considers project schedule as the research object, and discusses the difference between Ant Colony Optimization and other traditional algorithms in the process of solving Traveling-Salesman Problem (TSP). The author also finds out the advantages of Ant Colony Optimization on combinatorial optimization problems. Then according to the similarity of various types of project schedule, he attempts to make use of Ant Colony Optimization to solve the combinatorial optimization problems of the resources.In the second chapter, the author introduces some basic concepts of project management firstly, such as AON diagrams, critical path etc. Then the principle of Ant Colony Optimization is described in the following chapter, and several advanced algorithms,for example Genetic Algorithm and Simulated Annealing Algorithm , are also compared with Ant Colony Optimization when managing combinatorial optimization problems.In the fourth chapter, the author founds a set of models combined with an application example to solve the problems of resource optimization with Ant Colony Optimization, and uses the real data during his work to demonstrate the effectiveness of Ant Colony Optimization in resource optimization. The author uses a popular resource optimization method—parallel method in this example. Project schedule and resource allocation, which is made using two different optimization methods, is demonstrated in the form of charts. And it also proves that Ant Colony Optimization has the strength of rational resource allocation and maximally shortening the construction period.As the algorithm has been less used in project management till now, the author only tries to study on optimization related to one kind of resource in the project in this thesis. However Ant Colony Optimization is also adapted to solving multi-objective optimization, studying on this application direction has further research value and significance.