Z. Fang, J. Gao, and H. Li (PR China)
Multiobjective, knapsack problem, artificial immume system, quantum computing
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 similarity-based truncation algorithm, are employed to preserve the diversity of the population, and a new selection scheme 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.
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