To keep and improve the position of thermal power generation companies in the competitive market, performance evaluation is necessary. BSC is one of the most efficient performance evaluation models. This model has two assumptions of equal weights of perspectives and equal weights of performance evaluation indicators, which are not necessarily true in real-world problems. BWM is a strong method for weighting criteria in MADM problems. This research presents a trustable BWM algorithm for solving MADM problems with various indicators and hierarchical levels without considering the two mentioned assumptions. This algorithm can provide more trustable solutions for some real-world problems. Then, the weight of performance evaluation indicators of Fars Power Generation Management Company was evaluated by integrating the proposed algorithm with the BSC model. Seventeen performance evaluation indicators were identified in this company. Then, the identified indicators were classified and weighted in four perspectives using the BSC model. Based on the results, the integration of the proposed algorithm with the BSC model can be a suitable approach to assigning weights to indicators as per the performance evaluation of thermal power generation companies. Also, the algorithm is convergent and trustable and can provide reliable results for solving MADM problems according to various number of indicators and hierarchical level numbers.
