Chaos Quantum Clonal Multiobjective Evolutionary Algorithm

Abstract

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.