Abstract
This paper proposes an estimation approach for a commodity origin-destination matrix by using a sample commodity origin-destination (OD) matrix from a Commodity Flow Survey and also mode-specific OD matrices obtained from a transportation record of freight carriers. The proposed approach is formulated as a multi-objective bi-level optimization problem in which the upper-level seeks to minimize the sum of square deviation from the target matrices, while in the lower-level, user-equilibrium assignments of commodity OD matrix from a CFS and mode-specific OD matrices are performed. The developed model and the Genetic Algorithms-based solution algorithm were validated and tested on an intermodal transportation network of Korea. The results show that the model is able to produce an acceptable commodity OD matrix, implying that the proposed approach is applicable for a real-world problem.
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