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

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dc.citedby0
dc.contributor.authorIsmail N.L.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorDahlan N.Y.en_US
dc.contributor.authorMansor M.H.en_US
dc.contributor.authorSenthil Kumar A.V.en_US
dc.contributor.authorid57190935802en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid24483200900en_US
dc.contributor.authorid56372667100en_US
dc.contributor.authorid56888921600en_US
dc.date.accessioned2025-03-03T07:46:56Z
dc.date.available2025-03-03T07:46:56Z
dc.date.issued2024
dc.description.abstractThis 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.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-981-97-0372-2_7
dc.identifier.epage77
dc.identifier.scopus2-s2.0-85199156651
dc.identifier.spage71
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85199156651&doi=10.1007%2f978-981-97-0372-2_7&partnerID=40&md5=408a08b3900bc423a8ec40b97b60f674
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/37047
dc.identifier.volume10
dc.pagecount6
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleEnvironmental Science and Engineering
dc.subjectComputer programming
dc.subjectEconomic and social effects
dc.subjectElectric load dispatching
dc.subjectEvolutionary algorithms
dc.subjectMATLAB
dc.subjectCombined economic
dc.subjectCombined economic emission dispatch
dc.subjectEmission
dc.subjectEmission dispatch problem
dc.subjectGeneration cost
dc.subjectMatings
dc.subjectMulti objective
dc.subjectMulti-objectives optimization
dc.subjectOptimizers
dc.subjectTotal emissions
dc.subjectMultiobjective optimization
dc.titleSolving Combined Economic Emission Dispatch Problems Using Multi-objective Hybrid Evolutionary-Barnacles Mating Optimizationen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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