基于人类进化算法的背包问题求解方法

Solving Knapsack Problems by Human Evolutionary Algorithm

背包问题是计算机算法中的一个NP完备类困难问题,使用传统的优化方法在求解较大规模的背包问题时,都存在计算量大、迭代时间长的缺陷.人类进化算法是模拟人类进化机理而建立的一种智能优化算法,本文阐述了人类进化算法的基本原理和实现方法.为提高背包问题的求解速度和精度,将人类进化算法应用于背包问题的求解,演示了算法的工作过程.试验结果表明,使用该方法求解背包问题是完全可行的和有效的,与众多优化算法相比,人类进化算法具有更高的求解效率.

Knapsack problem is regarded as a difficult NP completeness problem in computer algorithms. When the knapsack problems with large scale are solved by traditional optimization methods, the computation is large and the iteration time is long. Human Evolutionary Algorithm （HEA） is an intelligent optimization algorithm simulating human evolutionary mechanism. The basic principle and realization method of this algorithm is discussed. In order to improve the speed and precision of the solution, Human evolutionary algorithm is used to solve Knapsack problems. The work process of algorithm is analyzed. The experimental results prove its feasibility and validity in solving Knapsack problems. Human evolutionary algorithm is more efficient compared with many other optimization algorithms.