Paper (22): Project Management Challenges in Road Infrastructure Development in Poland.
Abstract: There are numerous methods dedicated to supporting the decision-making process in the field of road infrastructure management. These methods are very effective in developing economies. In the case of a lack of infrastructure, they enable the determining of the most essential needs, the prediction of the consequences of decisions undertaken and the comparison of possible options. However, in developed economies the level of saturation by road infrastructure is usually high. Existing methods often cannot be effectively employed in order to support the decision-making process because all necessary infrastructure indicated by these methods has already been built. The differences in the consequences of possible decisions are very subtle and it is very difficult to carry out analyses which unequivocally indicates the optimal solutions. This paper presents the usage of machine learning as a tool in supporting the decision-making process in this area. The employment of machine learning enables predicting the consequences of analyzed decisions in examples where traditional methods do not produce satisfactory results.
Biography: Przemyslaw Sekula, Assistant Professor at University of Economics in Katowice (Poland). Since 2004 holds a Msc. Eng. in field of automatic control and robotics. Worked in industry and for government, chiefly as a project manager. Since 2012 Ph. D. in management. Sekula is interested in IT projects, infrastructure projects and machine learning.
