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基于递进式蚁群算法求解多目标汽车制造排程问题
引用本文:叶明,王宁生.基于递进式蚁群算法求解多目标汽车制造排程问题[J].中国机械工程,2006,17(14):1472-1476.
作者姓名:叶明  王宁生
作者单位:南京航空航天大学,南京,210016
基金项目:国家高技术研究发展计划(863计划)
摘    要:描述了多目标汽车排程问题的模型,提出了一个整体解决策略,即利用不同生产阶段间的缓冲区,通过基于改进的蚁群优化算法,实现多目标汽车队列优化以及有限柔性下的队列二次优化,递进式地求解该问题。提出运用蚁群算法解决以降低喷漆清洗成本和“重要选装件”使用率均衡为目标的汽车队列优化问题;设计了候选集—蚁群算法求解环形油漆车身缓冲区结构约束下的汽车队列二次优化问题。算例分析结果表明,提出的整体解决策略及算法具有有效性和优越性。

关 键 词:汽车排程问题(CSP)  多目标优化  蚁群优化(ACO)  油漆车身缓冲区
文章编号:1004-132X(2006)14-1472-05
收稿时间:2005-09-12
修稿时间:2005-09-12

A Step-ACO Algorithm for the Multi-objective Car Sequencing Problem
Ye Ming,Wang Ningsheng.A Step-ACO Algorithm for the Multi-objective Car Sequencing Problem[J].China Mechanical Engineering,2006,17(14):1472-1476.
Authors:Ye Ming  Wang Ningsheng
Affiliation:Nanjing University of Aeronautics and Astronautics, Nanjing, 210016
Abstract:This paper presented a model and the overall solutions for the multi-objective car sequencing problem.By the combination of multi-objective and single-objective sequencing optimization,we used the buffers between different production stages to solve this problem.First,we used ACO get the car sequence which satisfied the objectives of minimizing the costs of color purge and stability of high priority option usage rates. Then we designed Candidate-ACO to solve the CSP with limited flexibility under the round structure painted body storage.At last,data show that the proposed strategy and the algorithms are effective and useful.
Keywords:car sequencing problem(CSP)  multi-objective optimization  ant colony optimization(ACO)  PBS
本文献已被 CNKI 维普 万方数据 等数据库收录!
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