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Artificial Intelligence in Operational Research

  • Georgios I. Doukidis
  • Ray J. Paul
Textbook

Table of contents

  1. Front Matter
    Pages i-vii
    PDF

  2. Practical Experiences

    1. Front Matter
      Pages 1-1
      PDF
    2. Operational Research Participation in Artificial Intelligence: Practical Experiences
      Georgios I. Doukidis, Ray J. Paul
      Pages 3-7
    3. A Survey of the Application of Artificial Intelligence Techniques within the OR Society
      Georgios I. Doukidis, Ray J. Paul
      Pages 9-21
    4. From OR to Knowledge-based Systems: An Industrial Experience
      Helena Walters, Roger Schtaklef
      Pages 23-29
    5. A Five Hour Expert System Tutorial for Management Students
      P. N. Finlay, D. G. Johnson, M. King, C. J. Martin, G. J. Phythian
      Pages 31-44
    6. Experiences in Developing an Expert System for MBA Admissions
      Paul N. Finlay, Malcolm King
      Pages 45-55
    7. Exporting Know-how
      Jim Grassick
      Pages 57-59

  3. Application Areas

    1. Front Matter
      Pages 61-61
      PDF
    2. Combining Operational Research and Artificial Intelligence
      Georgios I. Doukidis, Ray J. Paul
      Pages 63-69
    3. An Artificial Intelligence Approach to Improving Computer Communications Network Topologies
      Samuel Pierre, Hai-Hoc Hoang
      Pages 71-84
    4. Multicriteria Analysis Represented by Artificial Intelligence Techniques
      Gabriella Balestra, Alexis TsoukiÀs
      Pages 85-96
    5. Using an Expert System to Monitor an Automatic Stock Control System
      J. C. Thorpe, A. Marr, R. S. Slack
      Pages 97-104
    6. Simple Expert Systems for Computer Assisted Instruction
      Malcolm King, Laurie McAulay
      Pages 105-113
    7. Fuzzy Ordinal Models for AI—OR
      I. B. Turksen
      Pages 115-126
    8. Administering Rule Development in Rule-based Expert Systems
      P. N. Finlay, Malcolm King, A. Burnett
      Pages 127-132

  4. Production Planning and Scheduling

    1. Front Matter
      Pages 133-133
      PDF
    2. Operational Research Approaches to Artificial Intelligence in Production Planning and Scheduling
      Ray J. Paul, Georgios I. Doukidis
      Pages 135-138
    3. The Scheduler’s Predictive Expertise: An Interdisciplinary Perspective
      K. N. McKay, J. A. Buzacott, N. Charness, F. R. Safayeni
      Pages 139-150
    4. A Knowledge-based Approach to Production Planning
      Peter Duchessi, Robert M. O’Keefe
      Pages 151-164
    5. An Expert System Framework for Economic Evaluation of Machining Operation Planning
      Guangming Zhang, Stephen C.-Y. Lu
      Pages 165-178
    6. An Integrated Framework for Generating and Revising Factory Schedules
      Stephen F. Smith, Peng Si Ow, Jean-Yves Potvin, Nicola Muscettola, Dirk C. Matthys
      Pages 179-192
    7. Distribution of Empty Railcars by an Expert System: A Case Study with Comparison with OR Approaches
      A. Beurrier, Ph. Demota, P. Levine, J.-Ch. Pomerol
      Pages 193-203
    8. Integration of AI and OR Techniques for Computer-aided Algorithmic Design in the Vehicle Routing Domain
      Jean-Yves Potvin, Guy Lapalme, Jean-Marc Rousseau
      Pages 205-213
    9. Expert Systems for Vehicle Scheduling
      C. D. J. Waters
      Pages 215-225

  5. Simulation

    1. Front Matter
      Pages 227-227
      PDF
    2. Artificial Intelligence and Expert Systems in Simulation Modelling
      Ray J. Paul, Georgios I. Doukidis
      Pages 229-238
    3. A Simulation and Learning Technique for Generating Knowledge about Manufacturing Systems Behavior
      Henri Pierreval, Henri Ralambondrainy
      Pages 239-252
    4. Replenishment at Sea
      T. M. Williams, R. P. Gittins, D. M. Burke
      Pages 253-259
    5. Knowledge-based Design and Simulation Environment (KBDSE): Foundational Concepts and Implementation
      Jerzy W. Rozenblit, Jhyfang Hu, Tag Gon Kim, Bernard P. Zeigler
      Pages 261-275
    6. Artificial Intelligence and Decision Analysis
      F. W. Dewhurst, E. A. Gwinnett
      Pages 277-285
    7. Is There a Place in OR for Intelligent Tutoring Systems?
      Marios C. Angelides, Georgios I. Doukidis
      Pages 287-299

  6. Methodology

    1. Front Matter
      Pages 301-301
      PDF
    2. Methodological Issues in Artificial Intelligence and Operational Research
      Georgios I. Doukidis, Ray J. Paul
      Pages 303-310
    3. A Problem-driven Approach to Expert System Development
      M. A. Rodger, John S. Edwards
      Pages 311-319
    4. Distributed Artificial Intelligence and Soft Systems: A Comparison
      Evangelos Kiountouzis, Christos Papatheodorou
      Pages 321-326
    5. Organizational Design: An Approach Incorporating Expert Systems
      J. H. Klein, P. L. Powell, N. A. D. Connell
      Pages 327-337
    6. A Comparison of Potential Applications of Expert Systems and Decision Support Systems
      N. A. D. Connell, P. L. Powell
      Pages 339-347
    7. Measuring Success and Failure in the Commercial Application of Expert Systems: ‘Hard’ Measures for ‘Soft’ Systems?
      N. A. D. Connell, P. L. Powell
      Pages 349-356
    8. Modelling Expertise for KBS Development
      I. M. Neale
      Pages 357-368

About this book

Keywords

artificial intelligence intelligence operational research scheduling simulation

Editors and affiliations

  • Georgios I. Doukidis
    • 1
  • Ray J. Paul
    • 2
  1. 1.Athens University of Economics and BusinessGreece
  2. 2.London School of Economics and Political ScienceUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-349-12362-9
  • Copyright Information Macmillan Publishers Limited 1992
  • Publisher Name Palgrave, London
  • eBook Packages Engineering
  • Print ISBN 978-1-349-12364-3
  • Online ISBN 978-1-349-12362-9
  • Buy this book on publisher's site
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