Multimodal Optimization: An Effective Framework for Model Calibration

Information Sciences, Forthcoming

37 Pages Posted: 24 Aug 2016 Last revised: 10 Dec 2016

See all articles by Manuel Chica

Manuel Chica

Open University of Catalunya (UOC) (Open University of Catalonia) - Internet Interdisciplinary Institute (IN3); The University of Newcastle, Australia

Jose Barranquero

Novelti

Tomasz Kajdanowicz

Wroclaw University of Technology

Sergio Damas

University of Granada

Oscar Cordon

University of Granada

Date Written: August 23, 2016

Abstract

Automated calibration is a crucial stage when validating non-linear dynamic systems. The modeler must control the calibration results and analyze parameter values in an iterative way. In many non-linear models, it is usual to find sets of configuration parameters that may obtain the same model fitting. In these cases, the modeler needs to understand the results’ implications and run a sensitivity analysis to check the model validity. This paper presents a framework based on niching genetic algorithms to provide modeler with a set of alternative calibration solutions which also ease the analysis of their parameters, model’s response, and sensitivity analysis. The framework is called MOMCA, an integral and interactive solution for model validation which facilitates the implication of decision makers. The core component of MOMCA is its niching genetic algorithm, able to reach various optima in multimodal optimization problems by keeping the necessary diversity. The proposed framework is applied to two different case studies. The first case study is a biological growth model and the second one is a managerial model to improve brand equity. Both applications show the benefits of the framework when providing a set of calibrated models and a way to analyze and perform sensitivity analysis based on the set of solutions.

Keywords: Model Calibration, Multimodal Optimization, Genetic Algorithms, Sensitivity Analysis

Suggested Citation

Chica, Manuel and Barranquero, Jose and Kajdanowicz, Tomasz and Damas, Sergio and Cordon, Oscar, Multimodal Optimization: An Effective Framework for Model Calibration (August 23, 2016). Information Sciences, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2828069 or http://dx.doi.org/10.2139/ssrn.2828069

Manuel Chica (Contact Author)

Open University of Catalunya (UOC) (Open University of Catalonia) - Internet Interdisciplinary Institute (IN3) ( email )

Barcelona
Spain

The University of Newcastle, Australia ( email )

University Drive
Callaghan, NSW 2308
Australia

HOME PAGE: http://www.manuchise.com

Jose Barranquero

Novelti ( email )

Madrid
Spain

Tomasz Kajdanowicz

Wroclaw University of Technology ( email )

ul. Smoluchowskiego 25
Wroclaw, 50-372
Poland

Sergio Damas

University of Granada ( email )

C/Rector López Argueta S/N
Granada, Granada 18071
Spain

Oscar Cordon

University of Granada ( email )

C/Rector López Argueta S/N
Granada, Granada 18071
Spain

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