Staff View: Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization

Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization

This paper introduces the Multi-objective Optimization Hybrid Evolutionary-Barnacles Mating Optimizer (MOHEBMO) algorithm, developed to solve multiple objectives simultaneously using the weighted sum method. MOHEBMO combines Evolutionary Programming and Barnacles Mating Optimizer to find the best tr...

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Main Authors:	Ismail N.L., Musirin I., Dahlan N.Y., Mansor M.H., Senthil Kumar A.V.
Other Authors:	57190935802
Format:	Conference paper
Published:	Springer Science and Business Media Deutschland GmbH 2025
Subjects:	Computer programming Economic and social effects Electric load dispatching Evolutionary algorithms MATLAB Combined economic Combined economic emission dispatch Emission Emission dispatch problem Generation cost Matings Multi objective Multi-objectives optimization Optimizers Total emissions Multiobjective optimization
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id	my.uniten.dspace-37047
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spelling	my.uniten.dspace-370472025-03-03T15:46:56Z Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Senthil Kumar A.V. 57190935802 8620004100 24483200900 56372667100 56888921600 Computer programming Economic and social effects Electric load dispatching Evolutionary algorithms MATLAB Combined economic Combined economic emission dispatch Emission Emission dispatch problem Generation cost Matings Multi objective Multi-objectives optimization Optimizers Total emissions Multiobjective optimization This paper introduces the Multi-objective Optimization Hybrid Evolutionary-Barnacles Mating Optimizer (MOHEBMO) algorithm, developed to solve multiple objectives simultaneously using the weighted sum method. MOHEBMO combines Evolutionary Programming and Barnacles Mating Optimizer to find the best trade-off among conflicting objectives. The algorithm is applied to the IEEE 30 Bus RTS with six generators, aiming to optimize total generation cost and total emission. Two case studies are conducted to evaluate the efficiency of the MOHEBMO, with simulations performed using MATLAB software. The algorithm's performance is compared with existing methods for solving non-convex multi-objective combined economic emission dispatch problems. The results indicate that MOHEBMO outperforms these existing algorithms, demonstrating its capability in determining the lowest optimal solution for both total generation cost and total emission. ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Final 2025-03-03T07:46:56Z 2025-03-03T07:46:56Z 2024 Conference paper 10.1007/978-981-97-0372-2_7 2-s2.0-85199156651 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199156651&doi=10.1007%2f978-981-97-0372-2_7&partnerID=40&md5=408a08b3900bc423a8ec40b97b60f674 https://irepository.uniten.edu.my/handle/123456789/37047 10 71 77 Springer Science and Business Media Deutschland GmbH Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Computer programming Economic and social effects Electric load dispatching Evolutionary algorithms MATLAB Combined economic Combined economic emission dispatch Emission Emission dispatch problem Generation cost Matings Multi objective Multi-objectives optimization Optimizers Total emissions Multiobjective optimization
spellingShingle	Computer programming Economic and social effects Electric load dispatching Evolutionary algorithms MATLAB Combined economic Combined economic emission dispatch Emission Emission dispatch problem Generation cost Matings Multi objective Multi-objectives optimization Optimizers Total emissions Multiobjective optimization Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Senthil Kumar A.V. Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization
description	This paper introduces the Multi-objective Optimization Hybrid Evolutionary-Barnacles Mating Optimizer (MOHEBMO) algorithm, developed to solve multiple objectives simultaneously using the weighted sum method. MOHEBMO combines Evolutionary Programming and Barnacles Mating Optimizer to find the best trade-off among conflicting objectives. The algorithm is applied to the IEEE 30 Bus RTS with six generators, aiming to optimize total generation cost and total emission. Two case studies are conducted to evaluate the efficiency of the MOHEBMO, with simulations performed using MATLAB software. The algorithm's performance is compared with existing methods for solving non-convex multi-objective combined economic emission dispatch problems. The results indicate that MOHEBMO outperforms these existing algorithms, demonstrating its capability in determining the lowest optimal solution for both total generation cost and total emission. ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
author2	57190935802
author_facet	57190935802 Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Senthil Kumar A.V.
format	Conference paper
author	Ismail N.L. Musirin I. Dahlan N.Y. Mansor M.H. Senthil Kumar A.V.
author_sort	Ismail N.L.
title	Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization
title_short	Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization
title_full	Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization
title_fullStr	Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization
title_full_unstemmed	Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization
title_sort	solving combined economic emission dispatch problems using multi-objective hybrid evolutionary-barnacles mating optimization
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2025
_version_	1825816082302107648
score	13.244109

Solving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimization

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