This paper proposes a hybrid version of the Salp Swarm Algorithm (SSA) and the hill climbing (HC) technique using various selection schemes to solve engineering design problems. The proposed algorithm consists of two stages. In the first stage, the basic SSA is hybridized with HC local search to improve its exploitation capabilities; we refer to the hybridized algorithm as HSSA. In the second stage, a selection scheme is applied to enhance the exploration capabilities of the hybrid SSA. Six popular selection schemes were investigated, and the proportional selection scheme was selected as it yielded the best performance. We refer to the hybridized SSA along with the proportional selection scheme as PHSSA. To validate the performance of the proposed algorithms, a series of experiments were conducted using thirty benchmark functions and four engineering design problems. The investigations using benchmark functions revealed that HSSA overcame the weaknesses of the local search in the basic SSA. Moreover, PHSSA enhanced performance by providing an appropriate balance between exploration and exploitation as well as maintaining the diversity of the solutions and avoiding premature convergence. Finally, PHSSA produced results on engineering design problems that were at least comparable and in many cases superior to SSA and similar algorithms in the literature.

中文翻译：

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混合 Salp Swarm 算法的选择方案敏感性：分析和应用

本文提出了一种混合版本的 Salp Swarm 算法 (SSA) 和爬山 (HC) 技术，使用各种选择方案来解决工程设计问题。所提出的算法由两个阶段组成。第一阶段，将基本SSA与HC局部搜索混合，提高其开发能力；我们将混合算法称为 HSSA。在第二阶段，应用选择方案来增强混合 SSA 的勘探能力。研究了六个流行的选择方案，选择了比例选择方案，因为它产生了最好的性能。我们将杂交 SSA 和比例选择方案称为 PHSSA。为了验证所提出算法的性能，使用三十个基准函数和四个工程设计问题进行了一系列实验。使用基准函数的调查表明，HSSA 克服了基本 SSA 中本地搜索的弱点。此外，PHSSA 通过在探索和开发之间提供适当的平衡以及保持解决方案的多样性和避免过早收敛来提高性能。最后，PHSSA 在工程设计问题上产生的结果至少具有可比性，并且在许多情况下优于 SSA 和文献中的类似算法。PHSSA 通过在探索和开发之间提供适当的平衡以及保持解决方案的多样性和避免过早收敛来提高性能。最后，PHSSA 在工程设计问题上产生的结果至少具有可比性，并且在许多情况下优于 SSA 和文献中的类似算法。PHSSA 通过在探索和开发之间提供适当的平衡以及保持解决方案的多样性和避免过早收敛来提高性能。最后，PHSSA 在工程设计问题上产生的结果至少具有可比性，并且在许多情况下优于 SSA 和文献中的类似算法。