基于一组自主水下航行器的非平稳物理场调查问题的群优化方法

A. Tolstikhin, I. Bychkov
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引用次数: 0

摘要

本文研究了寻找非平稳物理场源的问题。我们假设使用群算法可能适用于这种情况。提出了一种鲸优化算法和灰狼优化算法的混合算法。该算法与原始算法相比具有以下优点:对低维函数的优化问题能更精确地求解,且第一次迭代的收敛速度更快。为了使算法适应问题的要求,进行了两次修改。该算法作为一组自主水下航行器控制策略的基础。因此,在大多数情况下,小组可以在给定次数的搜索迭代中找到源。
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Swarm optimization approach to non-stationary physical field survey problem using a group of autonomous underwater vehicles
The paper considers the problem of searching for the source of a non-stationary physical eld. We assume that the use of swarm algorithms may be applicable in this case. A hybrid of the Whale Optimization Algorithm and Grey Wolf Optimizer is proposed in this paper. The algorithm has several advantages over its origins: a more precise solution of the optimization problem for low-dimensional functions and a higher convergence rate of the first iterations. Two modications were made to adapt the algorithm to the requirements of the problem. The proposed algorithm is used as a basis for a control strategy for a group of autonomous underwater vehicles. As a result, in the vast number of cases, the group can find the source within the given number of search iterations.
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