The logical precedence network planning of projects, considering the finish-to-start (FS) relations, using neural networks

One of the important steps in the process of project planning is the designing of logical precedence network. As the procedure of the logical precedence network planning is case dependent and varies in different projects, it could be considered as an unstructured and complex problem which should be solved by implementing the implicit domain knowledge of the planner. In this paper, we have shown how the artificial neural networks could be implemented to plan the finish-to-start logical precedence network of projects. The implementation results depict that the proposed methodology could result reasonable, accurate, and reliable outcomes, which could be used as a primary solution, which can enrich the acquired knowledge, after the accomplishment of the project and its practical corrections.