Therefore, the hybrid intelligence algorithm is effective to solve 0-1 knapsack problems.
因此，应用该混合智能算法求解0 - 1背包问题是比较有效的。
In this paper, we present an exact algorithm for solving nonseparable convex knapsack problems with linear constraints and bounded integer variables.
本文对线性约束不可分离凸背包问题给出了一种精确算法。
The numerical experimental results show that NSGA-II with the neighborhood search can outperform NSGA-II applied to multi-objective 0-1 knapsack problems.
数值实验表明，引入邻域搜索机制的NSGA - II算法在求解多目标0 - 1背包问题时表现出更好的性能。
Aiming at combinatorial optimization problems, this paper carries out the following main research work based on EDA. A hybrid EDA is proposed to solve the multidimensional knapsack problems (MKP).
本文针对组合优化问题，基于分布估计算法主要开展了如下研究：针对多维背包问题，设计了一种混合分布估计算法。
Aiming at combinatorial optimization problems, this paper carries out the following main research work based on EDA. A hybrid EDA is proposed to solve the multidimensional knapsack problems (MKP).
本文针对组合优化问题，基于分布估计算法主要开展了如下研究：针对多维背包问题，设计了一种混合分布估计算法。
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