离散鲸鱼算法求解拆解序列规划问题

工业产品的回收再制造有利于降低生产成本和保护环境, 而制定优秀的产品拆解序列规划提高拆解效率、降低回收成本为其关键. 针对回收设备在实际拆解中的因素, 建立一种基于离散鲸鱼算法(DWOA)的拆解序列规划模型. 该模型目标函数以位置改变为代价作为新的评价指标, 利用分层组合的方法快速生成初始群体. 离散鲸鱼算法具有优先保护约束交叉机制、启发式变异、优秀的全局和局部搜索能力. 以回收上橡皮板和空气围带进行对比实验, 结果表明在相同时间下, 离散鲸鱼算法的算法稳定性、寻优能力、收敛速度都要优于其他算法.

Disassembly Sequence Planning Using Discrete Whale Optimization Algorithm

Recycling and remanufacturing industrial products is conducive to reducing production costs and protecting the environment. It is very important to make excellent equipment disassembly sequence planning to improve disassembly efficiency and reduce recovery costs. For the factors of equipment recycling in actual disassembly, a disassembly sequence planning model based on a discrete whale optimization algorithm (DWOA) is proposed in this study. The objective function of the model employs the position change cost as the new evaluation indicator and adopts the stratified combination method to rapidly generate the initial population. DWOA features the precedence preservative crossover mechanism, heuristic mutation, and better global and local search ability. Comparative experiments are conducted with recycled upper rubber plate and standstill seal to test the feasibility of the proposed algorithm. The experimental results show that at the same time, the algorithm stability, optimization ability, and convergence speed of DWOA are better than those of other algorithms.