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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Bibliographic Details
Published inChinese physics letters Vol. 27; no. 1; pp. 37 - 40
Main Author 尚荣华 焦李成 李阳阳 吴建设
Format Journal Article
LanguageEnglish
Published IOP Publishing 2010
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
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ISSN0256-307X
1741-3540
DOI10.1088/0256-307X/27/1/010308

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Summary: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.
Bibliography:11-1959/O4
TP311.13
O224
ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0256-307X
1741-3540
DOI:10.1088/0256-307X/27/1/010308