This study aims to design a mathematical cost model for Blockchain Technology-enabled Supply Chain System (BT-enabled SCS), which may assist some companies that tend to evaluate the costs of BT as the main database in their SC system. We, therefore, identified the cost components of BT-enabled SCS based on the related literature review. The second purpose is to minimize the costs of the designed BT-enabled SCS model through Evolutionary Computation algorithms (CS/ACO/GA) as optimization techniques. To generate raw data for the model, the authors revised the Operations Research model and Inventory Management model as a mathematical formulation in Pharmaceutical Supply Chain. This mathematical formulation helps studies with a limitation of finding real data sets generate raw data in healthcare fields. Comparing CS/ACO/GA algorithms, the best solutions for the BT-enabled SCS cost model are CS and ACO with the higher Total Ranking Score (TRS) (scored by MSE, RMSE, and ROC), followed by GA standing in the second step. The more noteworthy finding is that all three algorithms have been able to find the global minimum for the BT-enabled SCS cost model with acceptable accuracy obtained from ROC.
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