Discover Scheduling Strategies with Gene Expression Programming for Dynamic Flexible Job Shop Scheduling Problem

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• 作者：Li Nie (1) nieli@meef.sspu.cn
  Yuewei Bai (1)
  Xiaogang Wang (1)
  Kai Liu (1)
• 关键词：gene expression programming &#8211 ; dynamic scheduling &#8211 ; flexible job shop scheduling
• 刊名：Lecture Notes in Computer Science
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：7332
• 期：1
• 页码：383-390
• 全文大小：247.0 KB
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• 作者单位：1. School of Mechanical & Electronic Engineering, Shanghai Second Polytechnic University, Jinhai Road 2360, Pudong District, Shanghai, 201209 People鈥檚 Republic of China
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In this paper, an intelligent approach based on gene expression programming (GEP) is proposed to discover scheduling strategies for dynamic flexible job shop scheduling problem (DFJSP). In the approach, an indirect encoding and decoding scheme is designed in which the concept of automatically defined functions (ADF) is introduced. In the evaluation of the proposed GEP-based approach, simulation experiments are conducted with respect to the objective of minimizing mean tardiness. The results show that GEP-based approach can automatically find more efficient scheduling strategies for DFJSP under a big range of processing conditions.