Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

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Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

Hiramatsu, Tomoru / Inoue, Hiroki / Kato, Yasuhiko

Highlights • Combination of the RAS method and the real-coded Genetic Algorithm for the interregional I–O table estimation. • Reduction of data source error. • Improved results from the RAS method’s estimation. • Performance evaluation experiment using the Japanese actual dataset.

Abstract In this paper, we propose a method for improving the accuracy of the estimation of interregional input–output tables, by combining the RAS method and the real-coded Genetic Algorithm (GA); these are simple representative methods for the estimation of an interregional input–output table. By comparing the performance evaluation results obtained using the proposed method, the RAS method, and Simulated Annealing, we verified that the combination of the genetic algorithm and the RAS method can enhance the estimation accuracy of an interregional input–output table. In addition, performance is further enhanced by adjusting GA parameters.