Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems
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Abstract
Based on the concept and principles of quantum computing and the principle of the immune clonal selection, a new algorithm for multi-objective 0/1 knapsack problems is introduced. In the algorithm, for the novel representation, qubit antibodies in the antibody population are updated by applying a new chaos update strategy. A quantitative metric is used for testing the convergence to the Pareto-optimal front. Simulation results on the 0/1 knapsack problems show that the new algorithm, in most cases, is more effective.
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SHANG Rong-Hua, JIAO Li-Cheng, LI Yang-Yang, WU Jian-She. Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems[J]. Chin. Phys. Lett., 2010, 27(1): 010308. DOI: 10.1088/0256-307X/27/1/010308
SHANG Rong-Hua, JIAO Li-Cheng, LI Yang-Yang, WU Jian-She. Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems[J]. Chin. Phys. Lett., 2010, 27(1): 010308. DOI: 10.1088/0256-307X/27/1/010308
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SHANG Rong-Hua, JIAO Li-Cheng, LI Yang-Yang, WU Jian-She. Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems[J]. Chin. Phys. Lett., 2010, 27(1): 010308. DOI: 10.1088/0256-307X/27/1/010308
SHANG Rong-Hua, JIAO Li-Cheng, LI Yang-Yang, WU Jian-She. Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems[J]. Chin. Phys. Lett., 2010, 27(1): 010308. DOI: 10.1088/0256-307X/27/1/010308
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