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作 者:张昕曜 喻明让[1] 陈云 Zhang Xinyao;Yu Mingrang;Chen Yun(School of Aeronautics and Astronautics,North University of China,Shanxi Taiyuan,030051,China;North Institute of Automatic Control Technology,Shanxi Taiyuan,030006,China)
机构地区:[1]中北大学航空宇航学院,山西太原030051 [2]北方自动控制技术研究院,山西太原030006
出 处:《机械设计与制造工程》2025年第4期33-36,共4页Machine Design and Manufacturing Engineering
摘 要:为了解决集成工艺规划与车间调度的多目标问题,建立了以最小化最大加工时间、最小化机器总负载、最小化瓶颈机器负载、最小化总拖期时间和最小化总过程时间的模型。首先针对建立的优化模型,提出一种混合麻雀搜索算法(SSA/SA),采用多元编码的方式表示问题的解。其次结合侦察者递减策略、Metropolis准则增强算法的局部搜索能力;使用Pareto更新最优解集策略,保存种群更新过程中的非支配解;引入多样性保持策略,避免算法收敛至单个解,提高算法性能;应用快速非支配排序方法作为麻雀种群的更新策略。最后通过测试实例检验所提出的方法,并与现有算法对比,证明了该方法在解决集成式工艺规划与车间调度(IPPS)问题方面的优越性。In order to solve the multi-objective problem of integrated process planning and scheduling,a model is established to minimize the maximum processing time,minimize the total machine load,minimize the bottleneck machine load,minimize the total delay time and the total process time.Firstly,according to the established optimization model,a hybrid sparrow search algorithm/simulated annealing(SSA/SA)algorithm is proposed,which uses multivariate coding to represent the solution of the problem.Secondly,the local search ability of the algorithm is enhanced by combining the scout decreasing strategy and the Metropolis criterion.The Pareto update optimal solution set strategy is used to preserve the non-dominant solution in the process of population renewal.The diversity preservation strategy is introduced to avoid the convergence of the algorithm to a single solution and improve the performance of the algorithm.Appling a fast non-dominant sorting method as an update strategy for sparrow populations,the proposed method is tested by test examples,and compared with the existing algorithms,it shows that the proposed method has the superiority in solving the problem of integrated process planning and scheduling(IPPS).
分 类 号:TP242.6[自动化与计算机技术—检测技术与自动化装置]
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