结合支配强度的NSGA-Ⅱ的柔性车间低碳调度

Low-carbon flexible shop scheduling based on dominant strength NSGA-II algorithm

针对加工辅助环节对传统柔性车间低碳调度的影响这一问题,以最大完工时间、碳排放及机器负载为目标,建立考虑机床上下料调整状态的柔性车间低碳调度模型,利用加权归一法进行量纲的统一;针对非支配排序遗传算法(Non-dominated Sorting Genetic Algorithm-Ⅱ,NSGA-Ⅱ)在解决高维多变量、复杂Pareto边界及复杂非线性多目标问题时存在无法识别非支配解、拥挤度公式不合理、计算效率低下及解集质量较差等问题,提出一种基于支配强度的改进NSGA-Ⅱ算法(Improved NSGA-Ⅱ algorithm based on Dominant Strength, INSGA-Ⅱ-DS)对该模型进行求解:将支配强度引入非支配排序,采用新型拥挤度算子与基于外部档案集的自适应精英保留策略;设计了一种变邻域搜索策略,扩大了邻域搜索范围,增强了算法的局部搜索能力。并运用实例数据对INSGA-Ⅱ-DS性能进行验证,结果表明,改进算法求解效率更高,解集质量更优。

Aiming at the problem of the influence of processing auxiliary links on the low-carbon scheduling of traditional flexible workshop,a flexible shop low-carbon scheduling model was established with the maximum completion time,carbon emission and machine load as the objective,and the dimension was unified by the weighted normalization method.In view of the problems of NSGA-II in solving high-dimensional multi-variable,complex pareto boundary and complex nonlinear multi-objective problems,such as inability to identify non-dominated solutions,unreasonable crowding distance formula,low computational efficiency and poor quality of solution set,etc.,an Improved NSGA-II algorithm based on Dominant Strength(INSGA-II-DS)was proposed to solve the model.The dominance strergth was introduced into non-dominated ranking,and a new crowding operator and an adaptive elite retention strategy based on external archive set were adopted.A variable neighborhood search strategy was designed to expand the neighborhood search scope and enhance the local search capability of the algorithm.The results show that the INSGA-II-DS has higher efficiency and better quality of solution set.