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

• Published in: Transportation research. Part E, Logistics and transportation review Vol. 95; pp. 385 - 402
• Main Authors: Hiramatsu, Tomoru, Inoue, Hiroki, Kato, Yasuhiko
• Format: Journal Article
• Language: English
• Published: Exeter Elsevier India Pvt Ltd 01.11.2016; Elsevier Sequoia S.A
• Subjects: Algorithms; Estimating techniques; Evolutionary computation; Genetic algorithm; Genetic algorithms; Input output analysis; Interregional input–output table; Iterative technique; Logistics; Matrix balancing; Parameter estimation; Performance evaluation; RAS method; Simulated annealing; Studies; Tables; Tables (data); Transportation; RAS method; Matrix balancing; Iterative technique; Genetic algorithm; Interregional input–output table; Evolutionary computation
• ISSN: 1366-5545; 1878-5794
• DOI: 10.1016/j.tre.2016.07.007

•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. 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.