A multi-granularity evolution based Quantum Genetic Algorithm for QoS multicast routing problem in WDM networks

Authors:
Huanlai Xing;Xin Liu;Xing Jin;Lin Bai;Yuefeng Ji
Affiliations:
Key Laboratory of Optical Communication and Lightwave Technologies, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication and Lightwave Technologies, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication and Lightwave Technologies, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication and Lightwave Technologies, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, PR China;Key Laboratory of Optical Communication and Lightwave Technologies, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, PR China
Venue:
Computer Communications
Year:
2009

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Abstract

QoS multicast routing problem in WDM networks is investigated, and an improved algorithm Multi-granularity Evolution based Quantum Genetic Algorithm (MEQGA) is proposed to address it. Based on Quantum Genetic Algorithm (QGA) with quantum rotation gate strategy, MEQGA introduces multi-granularity evolution mechanism, which allows different chromosomes of one generation to have different rotation angle step values to update. In term of this mechanism, MEQGA can significantly improve its capability of exploration and exploitation, since its optimization performance does not over-depend on the single rotation angle step scheme shared by all chromosomes any longer. MEQGA also presents an adaptive quantum mutation operation which is able to avoid local search efficiently. A repair method is applied to eliminate illegal graphs as many as possible hence more excellent solutions will appear in each evolutionary generation. Simulation results show that, for the QoS multicast routing problem, MEQGA outperforms other heuristic algorithms and is characterized by robustness, high success ratio, fast convergence and excellent capability on global searching.