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With analysis and research the traditional theory of solving knapsack problem, and then to optimize enigmatical knapsack problems, this paper proposed a new algorithm based on the absolute greedy and expected efficiency strategy. Through the three sets of simulation experiments, it shows that the algorithm can solve a class of knapsack problems and it is superior to greedy algorithm, backtracking algorithm, dynamic programming algorithm, branch and bound algorithm. The convergence speed is ten times as the artificial glowworm swam algorithm by comparing with these two algorithms. Finally, it analyzed discrete degree of data and determined an adaptive scope of the algorithm. 相似文献
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