DOI: 10.4018/IJAMC.2020070102 International Journal of Applied Metaheuristic Computing Volume 11 • Issue 3 • July-September 2020  Copyright©2020,IGIGlobal.CopyingordistributinginprintorelectronicformswithoutwrittenpermissionofIGIGlobalisprohibited.  41 Quantum-Behaved Bat Algorithm for Solving the Economic Load Dispatch Problem Considering a Valve-Point Effect Pandian Vasant, Universiti Teknologi Petronas, Seri Iskandar, Malaysia Fahad Parvez Mahdi, University of Hyogo, Kobe, Japan https://orcid.org/0000-0002-0081-7358 Jose Antonio Marmolejo-Saucedo, Universidad Panamericana, Facultad de Ingeniería, Ciudad de México, Mexico Igor Litvinchev, Nuevo Leon State University, San Nicolás de los Garza, Mexico https://orcid.org/0000-0002-1850-4755 Roman Rodriguez Aguilar, Universidad Panamericana, Escuela de Ciencias Económicas y Empresariales, Ciudad de México, Mexico Junzo Watada, Universiti Teknologi Petronas, Seri Iskandar, Malaysia ABSTRACT Quantumcomputing-inspiredmetaheuristicalgorithmshaveemergedasapowerfulcomputational tooltosolvenonlinearoptimizationproblems.Inthispaper,aquantum-behavedbatalgorithm (QBA)isimplementedtosolveanonlineareconomicloaddispatch(ELD)problem.Theobjective ofELDistofindanoptimalcombinationofpowergeneratingunitsinordertominimizetotal fuelcostofthesystem,whilesatisfyingallotherconstraints.Tomakethesystemmoreapplicable tothereal-worldproblem,avalve-pointeffectisconsideredherewiththeELDproblem.QBA isappliedin3-unit,10-unit,and40-unitpowergenerationsystemsfordifferentloaddemands. Theobtainedresultisthenpresentedandcomparedwithsomewell-knownmethodsfromthe literature such as different versions of evolutionary programming (EP) and particle swarm optimization(PSO),geneticalgorithm(GA),differentialevolution(DE),simulatedannealing (SA)andhybridABC_PSO.ThecomparisonofresultsshowsthatQBAperformsbetterthan the above-mentioned methods in terms of solution quality, convergence characteristics and computationalefficiency.Thus,QBAprovestobeaneffectiveandarobusttechniquetosolve suchnonlinearoptimizationproblem. KEywoRDS Economic Load Dispatch, Non-Convex, Optimization, Quantum-Behaved Bat Algorithm, Valve-Point Effect