The Application of Ant Colony Optimization in Investment Scheme of Construction Project

Large scale construction project is generally composed of several mutual correlative sub-projects. In the past, researchers usually divided the mutual effects such as sequential cost and time relationship between each sub-project pair, and chose the best project scheme only in the angle of isolated sub-project. The drawback is that it's difficult to attain the holistic construction project optimization. In view of this, this article adopt a new kind of random search optimization algorithm, the Ant Colony Optimization to tackle this problem. The article selected cost and time of construction project as research factors, and analyzed mutual influence relationship between each sub-project scheme, then made out the minimum investment cost function model of construction project. With respect to the entire combinatorial optimization for investment scheme, the article designed the GBAS (graph-based ant system, one kind of Ant Colony Optimization), and evaluated the combinatorial optimization investment scheme of construction project. The results indicate that the Ant Colony Optimization is more efficient than the Genetic Algorithm. It features strong optimization capability and maneuverability in searching the optimal investment scheme of construction project, and would have broad application in the field of construction project investment decision-making.