摘要
将工艺规划与车间调度进行有效的集成是解决制造系统中工艺规划与车间调度过程分开优化时设备利用率低以及生产效率差的问题的主要途径。为了实现绿色低碳制造,首先以制造过程中的碳排放最小化、最大完工时间最小化、总拖期时间最小化为优化目标,基于非线性工艺规划的原理,建立多目标集成式工艺规划与调度模型;然后采用NSGA-Ⅱ遗传算法进行求解,优化得到Pareto最优解集;并提出利用基于熵权法的TOPSIS决策方法从Pareto最优解集中选出最佳工艺路线与调度方案。最后结合案例,验证了该模型及求解过程的有效性,并为实际生产过程中车间调度方案的决策提供了依据。
Effective integration of process planning and shop scheduling is the main way to solve the problems of low equipment utilization and poor production efficiency when process planning and shop scheduling are optimized separately.In order to achieve green and low-carbon manufacturing,this paper firstly takes the minimization of total carbon emissions,the maximum time of completion and delay time in the manufacturing process as the optimization goals.Based on the principle of nonlinear process planning,a multi-objective integrated process planning is established.Then,the NSGA-Ⅱgenetic algorithm is used to solve the problem,and the Pareto optimal solution set is obtained by optimization;and the TOPSIS decision method based on the entropy weight method is proposed to select the optimal process route and scheduling scheme from the Pareto optimal solution set.Finally,combined with case,the validity of the model and the solution process is verified and also provides a basis for the decision of scheduling scheme in actual production process.
作者
杨庆斌
尹瑞雪
YANG Qingbin;YIN Ruixue(School of Mechanical Engineering,Guizhou University,Guiyang 550025,China)
出处
《组合机床与自动化加工技术》
北大核心
2023年第8期171-175,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金项目(51765010)。
关键词
NSGA-Ⅱ算法
TOPSIS排序法
集成式工艺规划与调度
多目标优化
NSGA-Ⅱgenetic algorithm
TOPSIS decision method
integration of process planning and scheduling(IPPS)
multi-objective optimizatio