A New Objective Method for Determining Criteria Weights in MCDM Models – LOGSTA

Determining criteria weights is the crucial part of the MCDM process as the weights significantly affect the ranking results of alternatives.Therefore, various techniques have been created to determine the weights of criteria, which are grouped into subjective, objective, and hybrid techniques.In this study, a new method based on LOGarithmic normalization and STAndard deviation (LOGSTA) is developed to determine objective criteria weights.The method has been described through two examples, one with square matrix (six alternatives and six criteria) and the second with seven alternatives and five criteria.The outcomes of the LOGSTA technique are compared with the Entropy, CRITIC, MEREC techniques to present the validity of results.LOGSTA shows various ranks although in some cases, it is fully correlated, which has been provided with SCC and WS correlation coefficients.The comparative analysis shows that the LOGSTA is efficient to determine objective weights of criteria.This method allows consideration of both types of criteria, a separate normalization process for benefit and cost criteria, and a different normalization procedure compared to other methods.