Comparison of genetic algorithm and dynamic programming solving knapsack problem

Yan Wang, M. Wang, Jia Li, Xiang Xu
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引用次数: 1

Abstract

In this paper, the genetic algorithm and the dynamic programming algorithm are used to solve the 0-1 knapsack problem, and the principles and implementation process of the two methods are analyzed. For the two methods, the initial condition values are changed respectively, and the running time, the number of iterations and the accuracy of the running results of each algorithm under different conditions are compared and analyzed, with the reasons for the differences are studied to show the characteristics in order to find different features of these algorithms.
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遗传算法与动态规划求解背包问题的比较
本文采用遗传算法和动态规划算法求解0-1背包问题,并分析了这两种方法的原理和实现过程。对于两种方法,分别改变初始条件值,对不同条件下各算法的运行时间、迭代次数和运行结果的精度进行比较分析,研究差异的原因,显示出其特点,从而发现这两种算法的不同特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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