The slime mould algorithm (SMA) has recently been introduced to solve continuous engineering problems, which has been employed to solve a wide range of various problems due to its good performance. This paper presents an enhanced binary SMA for solving the 0–1 knapsack problem at different scales. In the presented binary SMA, eight different transfer functions have been used and evaluated. The transfer function, which has performed better than others, has been proposed for the subsequent experiments. The Bitwise and Gaussian mutation operators are used to enhance the performance of the proposed binary SMA. Furthermore, a penalty function and a repair algorithm are used to handle infeasible solutions. The proposed method’s performance was evaluated statistically on 63 standard datasets with different scales. The obtained results from the proposed method were compared with ten state-of-the-art methods. The results indicated the superiority of the proposed methods.

最近引入了粘液模算法（SMA）来解决连续工程问题，由于其良好的性能，它已被用于解决范围广泛的各种问题。本文提出了一种用于解决不同尺度的 0-1 背包问题的增强型二元 SMA。在呈现的二进制 SMA 中，使用和评估了八种不同的传递函数。已经为后续实验提出了比其他人表现更好的传递函数。Bitwise 和 Gaussian 变异算子用于提高所提出的二元 SMA 的性能。此外，惩罚函数和修复算法用于处理不可行的解决方案。在 63 个不同尺度的标准数据集上对所提出的方法的性能进行了统计评估。从所提出的方法获得的结果与十种最先进的方法进行了比较。结果表明所提出方法的优越性。