The original Grand Canonical Monte Carlo (GCMC) molecular simulation method heavily relies on pure random steps for its various phases of displacement, removal and insertion. A new algorithm is presented in this article which employs the global optimization Ant Colony technique in a state-of-the-art algorithm to predict the adsorption isotherm of any adsorbate inside nanostructured adsorbents. Several experimentally measured isotherms are used from literature to successfully validate the proposed method. A detailed flowchart is presented to describe the entire algorithm. The Akaike information criterion is used as a part of the proposed method to determine the optimum number of required iterations. It was clearly demonstrated that our in-house ant colony molecular simulation (ACMS) method outperforms conventional GCMC method for all case studies. The simulation results also indicate that the newly proposed algorithm performs order of magnitude faster than GCMC with the same or better accuracies.

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