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This paper introduces a new, alternative approach for the analysis of power systems vulnerability based on a hybrid model that combines elements of the classical Deterministic Network Interdiction Problem (DNIP) with the use of an efficient multi-objective optimization evolutionary algorithm (MOEA). From a power systems perspective, the traditional DNIP is implemented as a surrogate approach to understand the interaction between the power system's component incapacitation (due to random failures or external attacks), and the system load shedding. The paper recognizes that, when analyzing power system vulnerability, it is possible to have multiple competing objectives and multiple prospective solutions that may change based on the preference of the decision-maker. This multi-objective view of the DNIP in the power systems context is solved using MOEA. As a result, the proposed approach could be used as an initial, straightforward screening approach to identify severe system disturbances. Several examples illustrate that the approach is able to reproduce and improve upon the results presented in previous studies.