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Presence of energy hubs in the future vision of energy networks creates a great opportunity for system planners and operators to move towards more efficient systems. The role of energy hubs as the intermediate in multi-carrier energy (MCE) systems calls for a generic framework to study the new upcoming technical as well as economical effects on the system performance. In response, this paper attempts to develop a general optimization and modeling framework for coupled power flow studies on different energy infrastructures. This, as a large-scale nonlinear problem, is approached through a robust optimization technique, i.e., multi-agent genetic algorithm (MAGA). The proposed procedure decomposes the multi-carrier optimal power flow (MCOPF) problem into its traditional separate OPF problem in such a way that the major advantages of simultaneous analysis of MCE systems would not be sacrificed. The presented scheme is then applied to an 11-hubs test system and introduces its expected applicability and robustness in the MCE systems analysis.