A hybrid fuzzy satisfying optimization model for sustainable gas resources allocation

Energy resources allocation continues to be a hot topic and has attracted more attention in recent years in Iran as one of the richest countries in the world in terms of hydrocarbon resources. Energy resources allocation is a multi-criteria decision making problem in which a great deal of input information cannot be expressed precisely. In this paper, we propose an integrated satisfying optimization approach based on Fuzzy Goal Programming (FGP) and Logarithmic Fuzzy Preference Programming (LFPP) the goal of which is to handle effectively the uncertainties and vagueness of input data and different importance preferences among fuzzy constraints and weights of objectives due to the above-mentioned problem. The proposed model is applied to a real case study of sustainable gas resources allocation in Iran. The solutions provide gas resources allocation to different sub-sectors at macro level taking various criteria into consideration. The results show that reasonable solutions that have been found are useful for supporting adjustment of the existing demand and supply patterns of gas resources, and also for coordination of conflict interactions among economic, security and environmental aspects of gas resources allocation.