改进粒子群算法在货物装载中的应用

An Application of Improved Particle Swarm Algorithms to Freighting Problem

本文采用改进粒子群算法求解货物装载问题。首先对传统背包问题进行分析,指出其在现实生活中存在的问题,提出了以最大价值为目标的更具现实意义的多目标模型,然后用粒子群算法进行求解,给出了一个算法求解的实验实例。在实现粒子群算法时,我们对基本粒子群算法进行了一些改进。实验证明采用这种改进的粒子群算法解决货物装载问题切实可行,有较高的搜索效率。

In this paper, a particle swarm algorithm was presented to solve the Freighting problem. Firstly, there are some limits in traditional knapsack problem algorithms in real world. We present a multi - objective model arming at largest value. Then we solved this problem with a Particle swarm Algorithm and experimented it use an example. In the example, we made some improvement to the basic particle swarm algorithm. The result of this experiment shows that this Particle Swarm Algorithm is available and efficient in solving Freighting problem.