AN ADAPTIVE MEMBRANE ALGORITHM FOR SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS-中国期刊网

摘要 Membranealgorithms(MAs),whichinheritfromPsystems,constituteanewparallelanddistributeframeworkforapproximatecomputation.Inthepaper,amembranealgorithmisproposedwiththeimprovementthattheinvolvedparameterscanbeadaptivelychosen.Inthealgorithm,somemembranescanevolvedynamicallyduringthecomputingprocesstospecifythevaluesoftherequestedparameters.Thenewalgorithmistestedonawell-knowncombinatorialoptimizationproblem,thetravellingsalesmanproblem.Theempiricalevidencesuggeststhattheproposedapproachisefficientandreliablewhendealingwith11benchmarkinstances,particularlyobtainingthebestoftheknownsolutionsineightinstances.Comparedwiththegeneticalgorithm,simulatedannealingalgorithm,neuralnetworkandafine-tunednon-adaptivemembranealgorithm,ouralgorithmperformsbetterthanthem.Inpractice,todesigntheairlinenetworkthatminimizethetotalroutingcostontheCABdatawithtwenty-fiveUScities,wecanquicklyobtainhighqualitysolutionsusingouralgorithm.

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AN ADAPTIVE MEMBRANE ALGORITHM FOR SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS

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AN ADAPTIVE MEMBRANE ALGORITHM FOR SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS

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