Quantum Interference Crossover-Based Clonal Selection Algorithm and Its Application to Traveling Salesman Problem

Hongwei DAI  Yu YANG  Cunhua LI  Jun SHI  Shangce GAO  Zheng TANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E92-D   No.1   pp.78-85
Publication Date: 2009/01/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E92.D.78
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Biocybernetics, Neurocomputing
clonal selection algorithm,  quantum interference crossover,  traveling salesman problem,  hybrid model,  

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Clonal Selection Algorithm (CSA), based on the clonal selection theory proposed by Burnet, has gained much attention and wide applications during the last decade. However, the proliferation process in the case of immune cells is asexual. That is, there is no information exchange during different immune cells. As a result the traditional CSA is often not satisfactory and is easy to be trapped in local optima so as to be premature convergence. To solve such a problem, inspired by the quantum interference mechanics, an improved quantum crossover operator is introduced and embedded in the traditional CSA. Simulation results based on the traveling salesman problems (TSP) have demonstrated the effectiveness of the quantum crossover-based Clonal Selection Algorithm.