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作 者:张炜 王丽娟 彭精立 Zhang Wei;Wang Lijuan;Peng Jingli(School of Intelligent Manufacturing,Xiamen City University,Xiamen,Fujian 361008,China)
机构地区:[1]厦门城市职业学院智能制造学院,福建厦门361008
出 处:《机电工程技术》2023年第11期38-42,共5页Mechanical & Electrical Engineering Technology
基 金:厦门市自然科学基金项目(3502Z20227432);福建省教育厅中青年教师教育科研项目(JAS22316);厦门城市职业学院高层次人才科研启动费资助项目(G2Q2022-7,G3R2022-8)。
摘 要:多目标优化问题(Multi-objective Optimization Problem,MOP)是针对两个或多个冲突目标的决策问题。传统的解决方案的顺序优化方法只能找到单个问题的最优解,很难获得整体最优解;而归一化方法以加权和的形式简化了复合冲突目标函数,但权重是高度主观的,且会牺牲一些目标,因而都难以得到理想的结果。MOP的目标是协调和合并所有目标。为此提出了一个多目标双层优化模型。通过两级层次优化机制建立了两个相互关联的目标之间的协调模型。针对双层规划模型,提出了一种双层嵌套遗传算法及其相应的编码策略。以一个混合模型焊装生产线的平衡和排序问题为例,将所提算法和传统归一化方法、顺序优化方法进行对比,证明了所提出的多目标双层优化模型的可行性和有效性。A multi-objective optimization problem(MOP)is a decision problem for two or more conflicting goals.Traditional solutions often use sequential optimization or normalization methods,which often make it difficult to achieve ideal results.The sequential optimization method only finds the optimal solution for a single problem,and it is difficult to obtain an overall optimality.The All-in-one approach simplifies a composite conflicting objective function in the form of a weighted sum.This kind of weighted solution based on preference weights is highly subjective and tends to sacrifice some goals.The goal of MOP is to coordinate and combine all goals.A multi-objective bilevel optimization model is proposed in this paper.A coordination model between two interconnected objectives is established by a two-level hierarchical optimization mechanism.Aiming at the bi-level programming model,a bi-level,nested genetic algorithm and its corresponding encoding strategy are developed.Taking a mixed model welding production line balance and scheduling problem as an example,the proposed algorithm is compared with traditional normalization methods and sequence optimization methods,proving the feasibility and effectiveness of the proposed multi-objective double-layer optimization model.
分 类 号:TG95[金属学及工艺—钳工工艺] TP18[自动化与计算机技术—控制理论与控制工程]
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