文件名称:Article_Demo1
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this research paper we present an immunological algorithm (IA) to solve global numerical optimization problems for high-dimensional instances. Such optimization problems are a crucial component for many real-world applications. We designed two versions of the IA: the first based on binary-code representation and the second based on real values, called opt-IMMALG01 and opt-IMMALG, respectively. A large set of experiments is presented to evaluate the effectiveness of the two proposed versions of IA. Both opt-IMMAL
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下载文件列表
ImmuneSimulation/Antibody.cs
ImmuneSimulation/AssemblyInfo.cs
ImmuneSimulation/bin/
ImmuneSimulation/bin/Debug/
ImmuneSimulation/bin/Debug/ImmuneSimulation.exe
ImmuneSimulation/FitnessFunction.cs
ImmuneSimulation/IAController.cs
ImmuneSimulation/ImmuneSimulation.csproj
ImmuneSimulation/ImmuneSimulation.sln
ImmuneSimulation/MainForm.cs
ImmuneSimulation/MainForm.Designer.cs
ImmuneSimulation/MainForm.resx
ImmuneSimulation/Program.cs
ImmuneSimulation/
ImmuneSimulation/AssemblyInfo.cs
ImmuneSimulation/bin/
ImmuneSimulation/bin/Debug/
ImmuneSimulation/bin/Debug/ImmuneSimulation.exe
ImmuneSimulation/FitnessFunction.cs
ImmuneSimulation/IAController.cs
ImmuneSimulation/ImmuneSimulation.csproj
ImmuneSimulation/ImmuneSimulation.sln
ImmuneSimulation/MainForm.cs
ImmuneSimulation/MainForm.Designer.cs
ImmuneSimulation/MainForm.resx
ImmuneSimulation/Program.cs
ImmuneSimulation/
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