An effective coding approach for multiobjective integrated resource selection and operation sequences problem
An effective coding approach for multiobjective integrated resource selection and operation sequences problem
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DOI：
10.1007/s10845-005-0012-y
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发表时间：
2006-08-01
影响因子：
8.3
通讯作者：
Seo, Yoonho
中科院分区：
文献类型：
--
作者：
Zhang, Haipeng;Gen, Mitsuo;Seo, Yoonho
本文研究了智能制造系统中的集成资源选择和操作序列问题。考虑到几种目标，其中订单的最大完工时间应最小化;机床之间的工作量应平衡;本地工厂中机器之间的总转换时间也应最小化。为了解决这一多目标iRS/OS模型，提出了一种新的基于双矢量的编码方法，通过设计包含两种信息的染色体来提高效率，即，操作顺序和机器选择。使用这种染色体，我们适应多级操作为基础的遗传算法（莫加）找到帕累托最优解。此外，一种特殊的技术，称为左移登山已被用来作为一种局部搜索，以提高我们的算法的效率。最后，对几个iRS/OS问题的实验结果表明，该方法能够获得最优解。此外，与以前的方法相比，莫加在寻找帕累托解方面表现得更好。
In this paper, we consider an integrated Resource Selection and Operation Sequences (iRS/OS) problem in Intelligent Manufacturing System (IMS). Several kinds of objectives are taken into account, in which the makespan for orders should be minimized; workloads among machine tools should be balanced; the total transition times between machines in a local plant should also be minimized. To solve this multiobjective iRS/OS model, a new two vectors-based coding approach has been proposed to improve the efficiency by designing a chromosome containing two kinds of information, i.e., operation sequences and machine selection. Using such kind of chromosome, we adapt multistage operation-based Genetic Algorithm (moGA) to find the Pareto optimal solutions. Moreover a special technique called left-shift hillclimber has been used as one kind of local search to improve the efficiency of our algorithm. Finally, the experimental results of several iRS/OS problems indicate that our proposed approach can obtain best solutions. Further more comparing with previous approaches, moGA performs better for finding Pareto solutions.