PT-TODIM Method for Probabilistic Linguistic MAGDM and Application to Industrial Control System Security Supplier Selection

The close combination of internet technology and traditional industrial control system (ICS) is a double-edged sword, which not only improves the accuracy of the control system, but also brings great danger. According to the statistics of the authoritative industrial security incident information database, Repository of Industrial Security Incidents (RISI), as of October 2011, there have been more than 200 attacks on industrial control systems around the world. It is obviously a multi-attribute decision-making (MADM) problem to select the appropriate industrial control system security supplier (ICSSS) for ensuring the safety of ICS. In this paper, the traditional TODIM method is improved and reconstructed in the probabilistic linguistic environment by incorporating the prospect theory (PT) which has received close attention recently. In this new model, the entropy weight method is used to obtain the attribute weight under complete information. And based on the ideas of PT as well as traditional TODIM method, the distortion of decision results caused by the risk attitude and psychological state of decision makers is corrected as far as possible. In my opinion, probabilistic linguistic term set (PLTS) ensures that the model can better cope with the real environment and the complexity and ambiguity of decision makers’ thinking. Finally, the successful application of this new probabilistic linguistic TODIM method based on PT (PT-PL-TODIM method) in the selection of ICSSS proves that the model is practical and is also of great value to the decision-making research related to ICS. Moreover, the comparative analysis between the proposed model and the existing model effectively confirms the reliability of the proposed method. In the future, it is hoped that this method can be successfully applied to more decision-making fields.