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A Comparative Study of Cuckoo Algorithm and Ant Colony Algorithm in Optimal Path Problems

机译:杜鹃算法与蚁群算法在最优路径问题中的比较研究

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Finding the optimal path can be realized through a wide range of algorithms, which is demanded in many fields. Among countless algorithms that are used for solving the optimal path problem, the ant colony optimization (ACO) is one of the algorithms used to solve the approximate optimal path solution, while the cuckoo search (CS) algorithm is a swarm intelligence algorithm featuring Levy flight, whose core idea is derived from the cuckoo nesting property. In order to provide more ideas and directions for future research on optimal path problems, this paper discusses in detail the advantages and disadvantages of the two algorithms for solving the optimal path problem and their scopes of application by comparing principles and flows of the two algorithms.
机译:寻找最佳路径可以通过多种算法来实现,这在许多领域都需要。在用于解决最佳路径问题的无数算法中,蚁群优化(ACO)是用于解决近似最佳路径解决方案的算法之一,而布谷鸟搜索(CS)算法是具有征费飞行的群体智能算法。 ,其核心思想源自杜鹃嵌套属性。为了给以后的最优路径问题研究提供更多的思路和方向,本文通过比较两种算法的原理和流程,详细讨论了两种算法在解决最优路径问题上的优缺点及其适用范围。

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