摘要
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.
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.
基金
Supported by the National High Technology Research and Development Program of China under Grant No 2009AA12Z210, the China Postdoctoral Science Foundation under Grant Nos 20080431228, 20090451369 and 200801426, the Natural Science Foundation of Shaanxi Province under Grant No 2009JQ8015, the National Natural Science Foundation of China under Grant Nos 60703108, 60703107 and 60803098.
