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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >Application of Hybrid Artificial Fish Swarm Algorithm Based on Similar Fragments in VRP
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Application of Hybrid Artificial Fish Swarm Algorithm Based on Similar Fragments in VRP

机译：基于相似片段的混合人工鱼群算法在VRP中的应用

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摘要

Focused on the issue that the decrease of convergence speed and the precision of calculation at the end of the process in Artificial Fish Swarm Algorithm(AFSA) and instability of results, a hybrid AFSA based on similar fragments is proposed. Traditional AFSA enjoys a lot of obvious advantages in solving complex optimization problems like Vehicle Routing Problem(VRP). AFSA have a few limitations such as low convergence speed, low precision and instability of results. In this paper, two improvements are introduced. On the one hand, change the definition of the distance for artificial fish, as well as increase vision field of artificial fish, and the problem of speed and precision can be improved when solving VRP. On the other hand, mix artificial bee colony algorithm(ABC) into AFSA - initialize the population of artificial fish by the ABC, and it solves the problem of instability of results in some extend. The experiment results demonstrate that the optimal solution of the hybrid AFSA is easier to approach the optimal solution of the standard database than the other two algorithms. In conclusion, the hybrid algorithm can effectively solve the problem that instability of results and decrease of convergence speed and the precision of calculation at the end of the process.
机译：针对人工鱼群算法（AFSA）收敛速度快，处理结束时计算精度低，结果不稳定等问题，提出了一种基于相似片段的混合AFSA算法。传统的AFSA在解决诸如车辆路径问题（VRP）之类的复杂优化问题时具有许多明显的优势。 AFSA具有一些局限性，例如收敛速度低，精度低和结果不稳定。本文介绍了两个改进。一方面，改变了人工鱼的距离定义，增加了人工鱼的视野，解决了VRP时可以解决速度和精度问题。另一方面，将人工蜂群算法（ABC）混合到AFSA中，通过ABC初始化人工鱼的种群，在一定程度上解决了结果不稳定的问题。实验结果表明，混合AFSA的最优解比其他两种算法更容易接近标准数据库的最优解。综上所述，该混合算法可以有效地解决结果不稳定，收敛速度降低，处理结束时计算精度高的问题。

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