0-1背包问题是组合优化中经典的NP难题,在蚁群算法的基础上结合量子计算提出一种求解0-1背包问题的量子蚁群算法。算法采用量子比特表示信息素,用量子旋转门来更新信息素。大量数据实例的比较测试表明,算法可有效提高蚂蚁算法的性能,减少搜索时间,具有更好的全局寻优能力。
0-1 knapsack problem is a typical NP-hard problem in combinatorial optimization.A quantum-inspired ant colony algorithm for solving the 0-1 knapsack problem is proposed which is based on the combination of ant colony optimization and quantum computing.In the algorithm,the pheromone is expressed by quantum bits,and quantum rotation gates are used to update the ant pheromone.Series of test instances validate the effectiveness of the algorithm.The proposed algorithm can reduce the searching time and has better performance in reaching the global optimum.