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This paper introduces how to improve the return loading rate problem by integrating the Sub-Tour reversal approach with the method of the Theory of Constraints (TOC). The proposed model generates the initial solution derived by the Sub-Tour reversal approach in phase 1 and then applies TOC to obtain the optimal solution, meeting the goal of improving the return loading rate to more than 50% and then lowering the total transportation distance in phase 2. To see our model capability, this study establishes an original distribution layout to compare the performance of the Sub-Tour reversal approach with our model, based on the simulation data generated by the Monte Carlo simulation. We also conduct the pair t-test to verify our model performance. The results show that our proposed model outperforms the Sub-Tour reversal approach in a significant manner. By utilizing the available data, our model can be easily implemented in the real world and efficiently seeks the optimal solutions.

Improving the Return Loading Rate Problem in Northwest China Based on the Theory of Constraints