文件名称:MO-MATLAB
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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-IMMALG01 and opt-IMMALG were extensively compared against several nature inspired meth
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YPEA124 MOEA-D
YPEA124 MOEA-D\license.txt
YPEA124 MOEA-D\MOEA-D
YPEA124 MOEA-D\MOEA-D\CreateSubProblems.m
YPEA124 MOEA-D\MOEA-D\Crossover.m
YPEA124 MOEA-D\MOEA-D\DecomposedCost.m
YPEA124 MOEA-D\MOEA-D\DetermineDomination.m
YPEA124 MOEA-D\MOEA-D\Dominates.m
YPEA124 MOEA-D\MOEA-D\license.txt
YPEA124 MOEA-D\MOEA-D\main.m
YPEA124 MOEA-D\MOEA-D\moead.m
YPEA124 MOEA-D\MOEA-D\MOP2.m
YPEA124 MOEA-D\MOEA-D\PlotCosts.m
YPEA124 MOEA-D\MOEA-D\ZDT.m
YPEA124 MOEA-D\license.txt
YPEA124 MOEA-D\MOEA-D
YPEA124 MOEA-D\MOEA-D\CreateSubProblems.m
YPEA124 MOEA-D\MOEA-D\Crossover.m
YPEA124 MOEA-D\MOEA-D\DecomposedCost.m
YPEA124 MOEA-D\MOEA-D\DetermineDomination.m
YPEA124 MOEA-D\MOEA-D\Dominates.m
YPEA124 MOEA-D\MOEA-D\license.txt
YPEA124 MOEA-D\MOEA-D\main.m
YPEA124 MOEA-D\MOEA-D\moead.m
YPEA124 MOEA-D\MOEA-D\MOP2.m
YPEA124 MOEA-D\MOEA-D\PlotCosts.m
YPEA124 MOEA-D\MOEA-D\ZDT.m