考虑零件分类的U型拆卸线平衡问题与改进烟花算法求解

An Improved Fireworks Algorithm for U-shaped Disassembly Line Balancing Problem Concerning Parts Classification

针对拆卸生产线中存在的不确定性和零件复杂性,构建以最小化工作站数、空闲指标、拆卸成本及零件分类指标的多目标数学模型并采用一种改进烟花算法对所提模型进行求解.首先,考虑所求解问题的特性对烟花算法进行离散化处理,重新定义了爆炸操作和变异操作,烟花个体产生爆炸火花和变异火花之后引入Pareto解集思想和NSGA-II拥挤距离机制对可行解进行筛选并更新烟花个体.其次,将所提烟花算法分别应用于求解中规模直线型和大规模U型拆卸线平衡问题算例中,并与其它算法的求解结果对比,验证改进烟花算法在直线型和U型拆卸线上的求解性能.最后,将所建模型和算法应用到打印机拆卸线中,并与直线型求解结果进行对比,对比结果表明所提方法有效可行.

In view of the uncertainties and the complexity of parts in the disassembly line,we build a multi-objective mathematics model that includes minimizing the number of workstations,idle index,disassembly cost,and the classification index and present an improved fireworks algorithm to solve it.First,we discretize the fireworks algorithm considering the characteristics of the problem to be solved and redefine the explosion operation and mutation operation.After the explosion and mutation sparks are generated by the fireworks individual,we use Pareto solution set and NSGA-II congestion distance mechanism to screen the feasible solution and update individual fireworks.Second,we use the proposed fireworks algorithm on the disassembly-line balancing problem of linear medium-scale and U-shaped large-scale examples and verify the performance of the improved fireworks algorithm by comparing it with other algorithms.Finally,we apply the model and algorithm to the printer disassembly line.The proposed mathematics model and algorithm are more effective and feasible than linear solutions.