Title: Multiple project portfolio scheduling using recurrent neural networks

Authors: Dimitrios C. Tselios; Ilias K. Savvas; M-Tahar Kechadi

Addresses: School of Computer Science and Informatics, University College of Dublin, Belfield, Dublin 4, Ireland ' Department of Computer Science and Telecommunications, TEI of Thessaly, Larissa 41110, Greece ' School of Computer Science and Informatics, University College of Dublin, Belfield, Dublin 4, Ireland

Abstract: 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.

Keywords: portfolio project management; job shop scheduling; recurrent neural networks; RNNs; multi-objective optimisation; greedy algorithm; IT portfolios; information technology; portfolio management.

DOI: 10.1504/IJSPM.2013.059421

International Journal of Simulation and Process Modelling, 2013 Vol.8 No.4, pp.227 - 240

Available online: 19 Feb 2014 *

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