Knapsack Problem

Trial designed recursive algorithm for solving knapsack problem.

试用递归方法设计求解背包问题的算法.

The simulated results show that QSE is superior to QEA and many traditional heuristic algorithms in solving a 0-1 knapsack problem.

在对0-1背包问题的求解中，表现出很好的性能。

This is about 01 knapsack problem dynamic programming algorithm.

这是关于01背包问题的动态规划算法.

According to thethe existed algorithms of 0-1 knapsack problem, a new non-recursive algorithm the paper.

针对目前求解0-1背包问题算法的优缺点, 开发了一种新的 非 递归算法.

Results of the numerical experiment show it is effective and useful in solving 0-1 knapsack problem.

仿真实验结果表明了该算法求解0-1背包问题的有效性与适用性.

The function optimization and 0-k knapsack problem experiments show that PEA has apparent superior in application area, searching capability and computation time compared with QEA and canonical genetic algorithm ( CGA).

函数优化和0-k背包问题实验表明，与量子进化算法和传统遗传算法相比，概率进化算法在适用范围、搜索能力和收敛速度上有明显的优势。

Hill Climbing Algorithm for Unconstraint Knapsack Problem

无限制背包问题的爬山算法

Backtracking to master the application of retrospective method with 0-1 knapsack problem.

掌握回溯法的应用用回溯法求解 0-1 背包问题.

The function optimization and knapsack problem show the effectiveness of PEA.

函数优化和背包问题实验验证了PEA的 有效性.