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- W2389333306 abstract "A new algorithm for multi-objective 0/1 knapsack problems is proposed.The antibodies in the antibody population are divided into dominated ones and non-dominated ones,which solves the diversity problem in the multi-objective optimization problems.In the algorithm,the clonal operation is adopted to implement the searching for optimal solutions in the global region and getting a widely spread Pareto-front.Then,adopting the immune gene operation the searching for optimal solutions is improved in the local region.In the last,the antibody repair operator is introduced for repairing the infeasible solutions produced by the immune gene operation,which guarantees the antibodies in the feasible region and implements the local research.Compared with the existed algorithms,the algorithm can obtain high quality solutions with good diversity,uniformity and convergence.Simulation results show that the Pareto-front obtained by the new algorithm has the most widely spread; the solutions obtained by the algorithm can converge to the Pareto-front and the spacing metric is depressed under 1%." @default.
- W2389333306 created "2016-06-24" @default.
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- W2389333306 date "2008-01-01" @default.
- W2389333306 modified "2023-10-03" @default.
- W2389333306 title "Clonal Selection Algorithm for Multi-Objective 0/1 Knapsack Problems" @default.
- W2389333306 hasPublicationYear "2008" @default.
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