Abstract The disposal of tailings is a vital process in mines. This study aims to address site selection issue of tailings pond using a suitable method. First, as different types of evaluation criteria exist, hybrid decision making information is considered. That is, crisp numbers are used to express quantitative values, while picture fuzzy numbers (PFNs) are suggested to describe qualitative information. Moreover, new comparison methods of PFNs are introduced to overcome the existing limitation. Considering the situation where weight information is partly known, a nonlinear optimization model is constructed. Then, to calculate criteria weights, the particle swarm optimization (PSO) algorithm is modified by introducing penalty functions. Afterwards, the weighted distance based approximation (WDBA) method is extended with hybrid evaluation information to rank alternatives. Last, the hybrid PSO-WDBA technique is applied in selecting the best tailings pond site in a gold mine. The effectiveness and advantages of this method are also verified through detailed discussions. The results show that the proposed evaluation model is dependable and effective, and can provide references for the site selection and management of tailings pond.

中文翻译：

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尾矿池选址的混合PSO-WDBA方法

摘要 尾矿处理是矿山的重要工序。本研究旨在使用合适的方法解决尾矿池的选址问题。首先，由于存在不同类型的评估标准，因此考虑混合决策信息。也就是说，使用清晰的数字来表示定量值，而建议使用图片模糊数 (PFN) 来描述定性信息。此外，引入了新的 PFN 比较方法以克服现有限制。考虑权重信息部分已知的情况，构建非线性优化模型。然后，为了计算标准权重，粒子群优化 (PSO) 算法通过引入惩罚函数进行修改。然后，基于加权距离的近似 (WDBA) 方法使用混合评估信息进行扩展，以对备选方案进行排名。最后，将混合 PSO-WDBA 技术应用于选择金矿的最佳尾矿池选址。这种方法的有效性和优点也通过详细的讨论得到验证。结果表明，所提出的评价模型可靠、有效，可为尾矿库选址和管理提供参考。