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基于改进遗传算法的铝合金型材下料方法研究.docx

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基于改进遗传算法的铝合金型材下料方法研究 Abstract： Withthecontinuousdevelopmentofsociety,aluminumalloyhasgraduallybecomeanessentialmaterialinpeople'slives.Intheautomotive,transportation,andconstructionindustries,theapplicationofaluminumalloyisextensive.Asakeystageinaluminumalloyprocessing,thecuttingmethodiscrucialforensuringthequalityoffinishedproducts.Duetothecharacteristicsofaluminumalloymaterials,traditionalcuttingmethodscancausesurfacedamage,processloss,andwasteofmaterials,whichnegativelyaffectsthequalityoffinishedproductsandincreasesproductioncosts. Therefore,improvingthecuttingmethodofaluminumalloyisessential.Inthispaper,weproposeacuttingmethodbasedonimprovedgeneticalgorithms,whichcaneffectivelyreducematerialwasteandimprovetheprocessingefficiency.Theexperimentresultsshowthattheproposedmethodcanincreasecuttingefficiencyby10%andreducematerialwasteby20%,comparedwithtraditionalmethods. Keywords:Aluminumalloy,cuttingmethod,geneticalgorithm,materialwaste,processingefficiency. Introduction： Inrecentyears,aluminumalloyhasbecomeapopularmaterialinvariousindustriesduetoitsexcellentproperties,suchaslightweight,highstrength,andcorrosionresistance.Duetotheincreasingdemandforaluminumalloy,itisnecessarytocontinuouslyimprovetheprocessingtechnologyofaluminumalloy.Amongthem,thecuttingmethodisacrucialprocessintheprocessingofaluminumalloy,whichdirectlyaffectsthequalityandefficiencyoffinishedproducts. Traditionalcuttingmethodsofaluminumalloy,suchassawing,milling,anddrilling,usuallyhavesomeshortcomings,suchashighmaterialwaste,lowprocessingefficiency,andsurfacedamage.Therefore,improvingthecuttingmethodofaluminumalloyisessential,andoptimizingthecuttingpathcaneffectivelyreducematerialwasteandimproveprocessingefficiency. Geneticalgorithms(GA)isacommonlyusedalgorithminthefieldofmathematicaloptimization.GAsimulatestheprocessofnaturalevolution,usingtheconceptofselection,crossover,andmutation,togeneratenewsolutionsuntiltheoptimalsolutionisfound.Thealgorithmhastheadvantagesoffastconvergence,norequirementforthei