Research and application of the crow search algorithm for geometric covering optimization problems

Grigory Tyrin, V. Frolovsky
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Abstract

The problem of geometric covering is a special case of the optimal design problem and belongs to the class of cutting and packing problems. The challenge is to position some geometric objects on the surface to be coated so that the entire surface is covered. The complexity of the problems under consideration is due to their belonging to the class of NP-hard problems, which excludes the possibility of solving them by exact methods and requires the development of approximate optimization methods and algorithms. This article discusses the problem of geometric covering of an area with circles from a given set of radii. To solve the problem of geometric covering, a hexagonal grid coverage method with optimization by a metaheuristic algorithm is used. The crow search algorithm is such an algorithm, which is a relatively new metaheuristic algorithm based on the intelligent behavior of crows in a flock. The crow search algorithm includes two control parameters: the awareness probability and the flight length. To study the solution method and check the efficiency, a problem was modeled on the basis of a real design of automatic irrigation systems, and the results of experiments with different values of control parameters were presented.
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乌鸦搜索算法在几何覆盖优化问题中的研究与应用
几何覆盖问题是优化设计问题的一种特殊情况,属于切割和包装问题。挑战在于将一些几何物体放置在要涂覆的表面上,从而覆盖整个表面。所考虑的问题的复杂性是由于它们属于np困难问题的类别,这排除了用精确方法解决它们的可能性,并且需要开发近似优化方法和算法。本文讨论了用给定半径集上的圆对一个区域进行几何覆盖的问题。为了解决几何覆盖问题,采用了一种基于元启发式算法优化的六边形网格覆盖方法。乌鸦搜索算法就是这样一种算法,它是一种相对较新的基于群中乌鸦智能行为的元启发式算法。乌鸦搜索算法包括两个控制参数:感知概率和飞行长度。为研究求解方法并验证其有效性,以实际自动灌溉系统设计为基础,对问题进行了建模,并给出了不同控制参数值下的实验结果。
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