<p>Recently, with developing the strategic industries that support Iran’s economy such as the oil, gas, and petrochemical (OGP) plants, it is very important to address the environmental problems caused by them. In this regard, groundwater has been polluted with light non-aqueous phase liquids (LNAPL) petroleum hydrocarbons more and more, and technologies for controlling groundwater polluted with LNAPL are of vital significance. However, making a robust decision under uncertainty for the problem of choosing the best technology among various technologies is difficult for users. To address this problem, the aim of the current work is to develop an innovative decision support system (DSS) for evaluating and choosing technologies to clean up groundwater impacted by LNAPL. The proposed DSS is based on integrating the sustainability and physically policies and the PSI (preference selection index) model under the probability hesitant fuzzy set (PHFS). An integrated criterion system, which involves nine criteria in four social, environmental, economic, and physically aspects has been suggested for evaluating the considered technologies. To implement the proposed DSS, seven technologies of Dual pump recovery, In-situ thermal remediation, In-situ soil mixing (stabilization), Air sparging/ soil vapor extraction, In-situ chemical oxidation, Phytotechnology, and Bioventing have been assessed. The evaluation results indicate that the technology of Air sparging/ soil vapor extraction is the best scenario for the clean-up of groundwater polluted by Iran’s OGP plants. The computation results demonstrate that the suggested DSS is feasible and applicable.</p>