N2 - The multicriteria decision process consists of five main steps: definition of the optimisation problem, determination of the weight structure of the decision criteria, design of the evaluation matrix, selection of the optimal evaluation method and ranking of solutions. It is often difficult to obtain the optimal solution to a multicriterion problem. The main reason is the subjective element of the model – the weight functions of the decision criteria. Expert opinions are usually taken into account in their determination. The aim of this article is to present a novel method of minimizing the uncertainty of the weights of the decision criteria using Monte Carlo simulation and method of data reconciliation. The proposed method is illustrated by the example of multicriterion social effectiveness evaluation for electric power supply to a building using renewable energy sources. L1 - http://www.czasopisma.pan.pl/Content/94714/PDF/06_paper.pdf L2 - http://www.czasopisma.pan.pl/Content/94714 PY - 2015 IS - No 1 March EP - 92 DO - 10.1515/aoter-2015-0006 KW - multicriteria optimization KW - weight uncertainty KW - photovoltaics A1 - Mendecka, Barbara A1 - Kozioł, Joachim PB - The Committee of Thermodynamics and Combustion of the Polish Academy of Sciences and The Institute of Fluid-Flow Machinery Polish Academy of Sciences DA - 2015[2015.01.01 AD - 2015.12.31 AD] T1 - Application of the method of data reconciliation for minimizing uncertainty of the weight function in the multicriteria optimization model SP - 83 UR - http://www.czasopisma.pan.pl/dlibra/publication/edition/94714 T2 - Archives of Thermodynamics