Chaos Quantum Clonal Multiobjective Evolutionary Algorithm

Based on the ergodicity of chaotic searching, the efficiency of quantum computing and antibody clonal selection theory of Artificial Immune System (AIS), Chaos Quantum Clonal Multiobjective Evolutionary Algorithm (CQCMEA) is proposed in this paper. The algorithm encodes the initial population by qub...

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Bibliographic Details
Published inIEEE conference anthology pp. 1 - 5
Main Authors She Xiangyang, Zhu Minghao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2013
Subjects
Algorithm design and analysis
Chaos
Clonal Select Algorithm
Evolutionary computation
Logic gates
Multiobjective optimization
Optimization
Qubit encoding
Sociology
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DOI10.1109/ANTHOLOGY.2013.6784763

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Summary:Based on the ergodicity of chaotic searching, the efficiency of quantum computing and antibody clonal selection theory of Artificial Immune System (AIS), Chaos Quantum Clonal Multiobjective Evolutionary Algorithm (CQCMEA) is proposed in this paper. The algorithm encodes the initial population by qubit, updates individual by quantum rotated gates with chaotic variables and maintains the distribution and diversity of solutions by crowding distance. Theoretical analysis and experimental simulation proved the effectiveness of the algorithm.
DOI:10.1109/ANTHOLOGY.2013.6784763