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PSO-based improved multi-flocks migrating birds optimization (IMFMBO) algorithm for solution of discrete problems

机译:基于PSO的改进的多群迁移鸟类优化(IMFMBO)算法解决离散问题

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摘要

In this paper, we proposed an improved migrating birds optimization algorithm to solve discrete problem. It is a metaheuristic search algorithm that is inspired by V formation during the migration of migratory birds. Proposed algorithm has two main modifications on basic migrating birds algorithm. Firstly, multi-flocks are used instead of single flock in order to avoid local minimum. Secondly, these flocks interact with each other for the more detailed search around flock that has got better solutions. This interaction is inspired by particle swarm optimization algorithm. Also, insertion method is used for neighborhood in migrating birds optimization algorithm. As a discrete problem, traveling salesman problem is chosen. Performance of the proposed algorithm is tested on some of symmetric benchmark problems from TSPLIB. Obtained results show that proposed method is superior to basic migrating birds algorithm.
机译:在本文中,我们提出了一种改进的迁移鸟优化算法来解决离散问题。 它是一种在迁移鸟类迁移过程中受V形成的启发。 建议算法对基本迁移鸟算法有两个主要修改。 首先,使用多群代替单羊群以避免局部最小。 其次,这些群体互相互动,以便围绕具有更好解决方案的群体搜索。 这种交互受到粒子群优化算法的启发。 此外,插入方法用于迁移鸟类优化算法中的邻域。 作为一个离散问题,选择了旅行的推销员问题。 所提出的算法的性能在TSPLIB的一些对称基准问题上进行了测试。 获得的结果表明,提出的方法优于基本迁移鸟算法。

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