Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems

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 ne...

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Veröffentlicht in:	Chinese physics letters 2010, Vol.27 (1), p.37-40
1. Verfasser:	尚荣华焦李成李阳阳吴建设
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Antibodies Convergence Knapsack problem Quantum computing Qubits (quantum computing) Representations Strategy 克隆选择算法多目标帕累托最优更新策略算法原理背包问题量子计算
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description	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.
doi_str_mv	10.1088/0256-307X/27/1/010308
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subjects	Algorithms Antibodies Convergence Knapsack problem Quantum computing Qubits (quantum computing) Representations Strategy 克隆选择算法多目标帕累托最优更新策略算法原理背包问题量子计算
title	Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems
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