Product disassembly and recycling are important issues in green design. Disassembly sequence planning (DSP) is an important problem in the product disassembly process. The core idea is to generate the best or approximately optimal disassembly sequence to reduce disassembly costs and time. According to the characteristics of the DSP problem, a new algorithm to solve the DSP problem is proposed. Firstly, a disassembly hybrid graph is introduced, and a disassembly constraint matrix is established. Secondly, the disassembling time, replacement frequency of disassembly tool and replacement frequency of disassembly direction are taken as evaluation criteria to establish the product fitness function. Then, an improved social engineering optimizer (SEO) method is proposed. In order to enable the algorithm to solve the problem of disassembly sequence planning, a swap operator and swap sequence are introduced, and steps of the social engineering optimizer are redefined. Finally, taking a worm reducer as an example, the proposed algorithm is used to generate the disassembly sequence, and the influence of the parameters on the optimization results is analyzed. Compared with several heuristic intelligent optimization methods, the effectiveness of the proposed method is verified.

中文翻译：

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使用Social Engineering Optimizer进行智能制造的拆卸顺序计划

产品的拆卸和回收是绿色设计中的重要问题。拆卸顺序计划（DSP）是产品拆卸过程中的重要问题。核心思想是生成最佳或近似最佳的拆卸顺序，以减少拆卸成本和时间。根据DSP问题的特点，提出了一种解决DSP问题的新算法。首先，引入了一个分解混合图，并建立了分解约束矩阵。其次，以拆卸时间，拆卸工具的更换频率和拆卸方向的更换频率为评估标准，建立了产品适应度函数。然后，提出了一种改进的社会工程优化器（SEO）方法。为了使算法能够解决拆卸序列计划问题，引入了交换运算符和交换序列，并重新定义了社会工程优化器的步骤。最后以蜗轮蜗杆减速器为例，提出的算法用于生成反汇编序列，并分析了参数对优化结果的影响。通过与几种启发式智能优化方法的比较，验证了该方法的有效性。