A multi-Objective Optimisation Metaheuristic Hybrid technique for Forecasting the Electricity Consumption of the UAE: A Grey Wolf Approach

Andreas Karathanasopoulos, Chia Chun Lo, Sovan Mitra, Mohamed Osman, Hans-Jörg von Mettenheim and Slim Skander 2024. A multi-Objective Optimisation Metaheuristic Hybrid technique for Forecasting the Electricity Consumption of the UAE: A Grey Wolf Approach. Journal of Forecasting. Advanced online publication. https://doi.org/10.1002/for.3187

TitleA multi-Objective Optimisation Metaheuristic Hybrid technique for Forecasting the Electricity Consumption of the UAE: A Grey Wolf Approach
TypeJournal article
AuthorsAndreas Karathanasopoulos, Chia Chun Lo, Sovan Mitra, Mohamed Osman, Hans-Jörg von Mettenheim and Slim Skander
Abstract

By implementing a multi-objective optimization approach in forecasting, we introduce three optimization models grey wolf optimizer, genetic algorithm, and differential evolution algorithm combined with multilayer perceptron neural networks and support vector machines to predict electricity consumption in the UAE. The hybrid models' accuracy and efficiency were evaluated using various forecasting metrics. This study's contributions are threefold: it is the first to employ such a sophisticated hybrid approach, particularly using the recently introduced grey wolf optimizer, it compares optimization techniques with the established Pearson correlation-based method for dimensionality reduction and it represents one of the most extensive macroeconomic forecasts in the UAE using multi-objective heuristic hybrid optimization methods. Our findings indicate that the grey wolf optimizer significantly outperforms all other models, followed by the genetic algorithm.

JournalJournal of Forecasting
ISSN1099-131X
Year2024
PublisherWiley
Digital Object Identifier (DOI)https://doi.org/10.1002/for.3187
Publication dates
Published in print23 Aug 2024

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