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Flow-Shop Scheduling Models with Parameters Represented by Rough Variables

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In reality, processing times are often imprecise and this imprecision is critical for the scheduling procedure. This research deals with flow-shop scheduling in rough environment. In this type of scheduling problem, we employ the rough sets to represent the job parameters. The job processing times are assumed to be rough variables, and the problem is to minimize the makespan. Three novel types of rough scheduling models are presented. A rough simulation-based genetic algorithm is designed to solve these models and its effectiveness is well illustrated by numerical experiments.

schedulingflow-shoprough setrough simulationrough programminghybrid intelligent algorithm

彭锦、Kakuzo Iwamura

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Department of Mathematical Sciences, State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, China

Department of Mathematics, Josai University, Sakado, Saitama 350-0295, Japan

国家自然科学基金Sino-French Joint Laboratory for Research in Computer Science, Control and Applied Mathematics (LIAMA)国家重点项目湖北省教育厅科研项目

601740492001A43007

2003

清华大学学报自然科学版(英文版)
清华大学

清华大学学报自然科学版(英文版)

EI
影响因子：0.474
ISSN：1007-0214
年,卷(期)：2003.8(1)
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