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AI and OR in management of operations: history and trends

Kobbacy, KAH, Vadera, S and Rasmy, MH 2007, 'AI and OR in management of operations: history and trends' , Journal of the Operational Research Society, 58 (1) , pp. 10-28.

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      Abstract

      The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested.

      Item Type: Article
      Uncontrolled Keywords: Operations management, artificial intelligence, operational research
      Themes: Subjects / Themes > H Social Sciences > HD Industries. Land use. Labor > HD0028 - 0070 Management. Industrial Management
      Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science
      Subjects / Themes > T Technology > TS Manufactures > TS155-194 Production management. Operations management
      Subjects outside of the University Themes
      Schools: ?? sch_sbs ??
      Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
      Journal or Publication Title: Journal of the Operational Research Society
      Publisher: Palgrave Macmillan
      Refereed: Yes
      ISSN: 01605682
      Depositing User: H Kenna
      Date Deposited: 21 Aug 2007 14:52
      Last Modified: 20 Aug 2013 16:46
      URI: http://usir.salford.ac.uk/id/eprint/274

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