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- W2381213284 abstract "The existing methods for automatic cotton blending cannot handle large-size problems or find the best solutions easily.A mathematic model for multi-constrained automatic cotton blending was set up.A hybrid genetic algorithm(MGA1) based on the adaptive penalty function was proposed,which used the penalty function to handle multi-constraints,and improved the rate of population revolution by monitoring the extent of population revolution and increasing the selection pressure properly.Furthermore,another hybrid genetic algorithm(MGA2) based on the simulated annealing algorithm and the atavistic strategy was proposed.Experiments were carried out to verify the proposed algorithms using the actual raw cotton stock and quality data from an enterprise.For the automatic cotton blending problem with middle and small size,MGA2 is better to find the optimum and diversiform solutions.For the automatic cotton blending problem with larger size,MGA1 can keep better astringency.And the solutions found by MGA1 are better than those of MGA2.Using MGA1 and MGA2 synthetically can satisfy different demands of cotton enterprises." @default.
- W2381213284 created "2016-06-24" @default.
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- W2381213284 date "2009-01-01" @default.
- W2381213284 modified "2023-09-24" @default.
- W2381213284 title "Hybrid genetic algorithm for multi-constrained automatic cotton blending" @default.
- W2381213284 hasPublicationYear "2009" @default.
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