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

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  • Hiramatsu, Tomoru
  • Inoue, Hiroki
  • Kato, Yasuhiko

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.

Suggested Citation

  • Hiramatsu, Tomoru & Inoue, Hiroki & Kato, Yasuhiko, 2016. "Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 385-402.
    • Handle: RePEc:eee:transe:v:95:y:2016:i:c:p:385-402
    DOI: 10.1016/j.tre.2016.07.007
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    7. Cristian Mardones & Darling Silva, 2023. "Evaluation of Non-survey Methods for the Construction of Regional Input–Output Matrices When There is Partial Historical Information," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1173-1205, March.

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