A quantum-inspired artificial immune system for multiobjective 0-1 knapsack problems

Authors:
Jiaquan Gao;Lei Fang;Guixia He
Affiliations:
Zhijiang College, Zhejiang University of Technology, Hangzhou, China;Zhijiang College, Zhejiang University of Technology, Hangzhou, China;Zhijiang College, Zhejiang University of Technology, Hangzhou, China
Venue:
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Year:
2010

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Abstract

In this study, a novel quantum-inspired artificial immune system (MOQAIS) is presented for solving the multiobjective 0-1 knapsack problem (MKP) The proposed algorithm is composed of a quantum-inspired artificial immune algorithm (QAIS) and an artificial immune system based on binary encoding (BAIS) On one hand, QAIS, based on Q-bit representation, is responsible for exploration of the search space by using clone, mutation with a chaos-based rotation gate, update operator of Q-gate On the other hand, BAIS is applied for exploitation of the search space with clone, a reverse mutation Most importantly, two diversity schemes, suppression algorithm and truncation algorithm with similar individuals (TASI), are employed to preserve the diversity of the population, and a new selection scheme based on TASI is proposed to create the new population Simulation results show that MOQAIS is better than two quantum-inspired evolutionary algorithms and a weight-based multiobjective artificial immune system.