Multiple project portfolio scheduling using recurrent neural networks

This work is devoted to the portfolio project management problem and more precisely it is focused on IT portfolios' management. The problem is modelled as a multi‐purpose job shop problem. Contemporary organisations such as IT companies define a careful planning to perform a set of projects that share common resources. These projects must, therefore, be handled concurrently. In this study we reviewed the literature and developed a system based on a multi‐objective problem model. We use recurrent neural network (RNN) technique to look for optimal or near‐optimal solutions to the derived optimisation problem. We first apply a greedy algorithm to find an initial feasible solution. This solution is then fed to the RNN. We implemented our approach and evaluated it on some well known benchmarks. The experimental results obtained were very promising.