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Adaptiveconstrainedparticleswarm

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  • Update : 2012-11-26
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Considering that theparticleswarmoptimization( PSO) algorithmcanbeeasily trappedinto the local minimal valueinconstrainedoptimizationproblems, amodifiedconstrainedparticleswarmoptimiza tionalgorithmwasproposed. Theobjective functionvalue andthe violationvalue of constraint functions wereeffectively combinedto formtwofitnesses, andthefitnesseswereadoptedto estimate if theparticle wassuperior or not ina dynamicway. Theadaptiveweight functionwasadoptedinthe calculationof the violationvalue. The strategy of keeping anadaptive relationof weight coefficientswasproposed, andthe strategyof swarmtournament selectionwasimproved. Theapplicationlocalizationsof thesinglefitnessof PSOwerewidenedaswell. ThemodifiedconstrainedPSOalgorithmwasappliedtosolveenergyoptimiza tionproblemsof theurbanwater supplyprocess, whichshowedthat theconvergent speedof thealgorithm isfast andthe result isvalid. Afeasibleapproachto solvetheindustrial constraint optimizationproblems withPSOwasprovided.
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