In this article, a new quantum social spider optimization (QSSO) algorithm is proposed. In the QSSO algorithm, we introduce an encoding approach based on bits described on social spider optimization (SSO) and serves as the evolution method of the population space. For the encoding of individuals, the probability amplitude expression of quantum bit is applied to describe the position of individuals, by which one individual's position can be expressed as the superposition of multistates. In such a way, the population diversity and the global searching capability of the SSO algorithm are enhanced. The QSSO algorithm was used to optimize the hydropower station dispatch, and the calculation results show that QSSO algorithm has fast convergence, small number of tuning parameters, high calculation accuracy, stability, simple, and is easy to be implemented with strong global search capability.

中文翻译：

---

基于量子社会蜘蛛优化算法的水电站调度优化

在本文中，提出了一种新的量子社交蜘蛛优化（QSSO）算法。在QSSO算法中，我们引入了一种基于社交蜘蛛优化（SSO）描述的比特的编码方法，作为种群空间的演化方法。对于个体的编码，利用量子比特的概率幅表达式来描述个体的位置，将个体的位置表示为多态的叠加。这样，增强了 SSO 算法的种群多样性和全局搜索能力。将QSSO算法用于水电站调度优化，计算结果表明QSSO算法收敛速度快、整定参数少、计算精度高、稳定性好、操作简单、