Differential evolution algorithm of solving an inverse problem for the spatial Solow mathematical model

Sergey Kabanikhin; Olga Krivorotko; Zholaman Bektemessov; Maktagali Bektemessov; Shuhua Zhang

doi:10.1515/jiip-2020-0108

Differential evolution algorithm of solving an inverse problem for the spatial Solow mathematical model

Sergey Kabanikhin, Olga Krivorotko, Zholaman Bektemessov, Maktagali Bektemessov, Shuhua Zhang

Research output: Contribution to journal › Article › peer-review

Abstract

The differential evolution algorithm is applied to solve the optimization problem to reconstruct the production function (inverse problem) for the spatial Solow mathematical model using additional measurements of the gross domestic product for the fixed points. Since the inverse problem is ill-posed the regularized differential evolution is applied. For getting the optimized solution of the inverse problem the differential evolution algorithm is paralleled to 32 kernels. Numerical results for different technological levels and errors in measured data are presented and discussed.

Original language	English
Pages (from-to)	761-774
Number of pages	14
Journal	Journal of Inverse and Ill-Posed Problems
Volume	28
Issue number	5
Early online date	1 Sep 2020
DOIs	https://doi.org/10.1515/jiip-2020-0108
Publication status	Published - 1 Oct 2020

Keywords

differential evolution
economy
identifiability
inverse problem
optimization
parameter identification
PDE
reconstruction of parameters
regularization
Solow model
spatial Solow model

OECD FOS+WOS

1.01 MATHEMATICS

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10.1515/jiip-2020-0108

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title = "Differential evolution algorithm of solving an inverse problem for the spatial Solow mathematical model",

abstract = "The differential evolution algorithm is applied to solve the optimization problem to reconstruct the production function (inverse problem) for the spatial Solow mathematical model using additional measurements of the gross domestic product for the fixed points. Since the inverse problem is ill-posed the regularized differential evolution is applied. For getting the optimized solution of the inverse problem the differential evolution algorithm is paralleled to 32 kernels. Numerical results for different technological levels and errors in measured data are presented and discussed. ",

keywords = "differential evolution, economy, identifiability, inverse problem, optimization, parameter identification, PDE, reconstruction of parameters, regularization, Solow model, spatial Solow model",

author = "Sergey Kabanikhin and Olga Krivorotko and Zholaman Bektemessov and Maktagali Bektemessov and Shuhua Zhang",

year = "2020",

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doi = "10.1515/jiip-2020-0108",

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AU - Kabanikhin, Sergey

AU - Krivorotko, Olga

AU - Bektemessov, Zholaman

AU - Bektemessov, Maktagali

AU - Zhang, Shuhua

PY - 2020/10/1

Y1 - 2020/10/1

N2 - The differential evolution algorithm is applied to solve the optimization problem to reconstruct the production function (inverse problem) for the spatial Solow mathematical model using additional measurements of the gross domestic product for the fixed points. Since the inverse problem is ill-posed the regularized differential evolution is applied. For getting the optimized solution of the inverse problem the differential evolution algorithm is paralleled to 32 kernels. Numerical results for different technological levels and errors in measured data are presented and discussed.

AB - The differential evolution algorithm is applied to solve the optimization problem to reconstruct the production function (inverse problem) for the spatial Solow mathematical model using additional measurements of the gross domestic product for the fixed points. Since the inverse problem is ill-posed the regularized differential evolution is applied. For getting the optimized solution of the inverse problem the differential evolution algorithm is paralleled to 32 kernels. Numerical results for different technological levels and errors in measured data are presented and discussed.

KW - differential evolution

KW - economy

KW - identifiability

KW - inverse problem

KW - optimization

KW - parameter identification

KW - PDE

KW - reconstruction of parameters

KW - regularization

KW - Solow model

KW - spatial Solow model

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M3 - Article

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SP - 761

EP - 774

JO - Journal of Inverse and Ill-Posed Problems

JF - Journal of Inverse and Ill-Posed Problems

SN - 0928-0219

IS - 5

ER -

Differential evolution algorithm of solving an inverse problem for the spatial Solow mathematical model

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Keywords

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