Skip to main content
SpringerLink
Log in

Integrating AI and OR: An Industrial Engineering Perspective

  • Conference paper
Advances in Information Systems (ADVIS 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3261))

Included in the following conference series:

Abstract

Many researchers have spent significant effort in developing techniques for solving hard combinatorial optimization problems. We see that both the Operations Research (OR) and the Artificial Intelligence (AI) communities are interested in solving these types of problems. OR focuses on tractable representations, such as linear programming whereas AI techniques provide richer and more flexible representations of real world problems. In this paper, we attempt to demonstrate the impressive impact of OR and AI integration. First we discuss opportunities for integration of OR and AI. Then three applications are presented to demonstrate how OR and AI are integrated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Luss, H., Rosenwein, M.B.: Operations Research Applications: Opportunities and Accomplishments. European Journal of Operational Research 97, 220–244 (1997)

    Article  MATH  Google Scholar 

  2. Simon, H.A.: Two heads are Better than One: The Collaboration between AI and OR. Interface 17, 8–15 (1987)

    Article  Google Scholar 

  3. CONDOR Committee On the Next Decade in Operations Research: Operations Research: The Next Decade, Anonymous. Operations Research 36, 619–637 (1988)

    Google Scholar 

  4. Klee, V., Minty, G.: How Good is the Simplex Algoritm. In: Shisha, O. (ed.) Inequalities –III, pp. 159–175. Academic Press, New York (1972)

    Google Scholar 

  5. Khachiyan, L.G.: A Polynomial Time Algorithm for Linear Programming. Math Doklady 20, 191–194 (1979)

    MATH  Google Scholar 

  6. Karmarkar, N.: A New Polynomial Time Algorithm for Linear Programming. Combinatorica 4, 373–395 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  7. Lustig, I.J., Marsten, R.E., Shannon, D.F.: Interior-point Methods for Linear Programming: Computational State of the Art. ORSA Journal on Computing, 1–4 (1994)

    Google Scholar 

  8. ILOG: ILOG CPLEX 8.0 User’s Manual. Gentilly France (2002)

    Google Scholar 

  9. Gomes, C.P.: Artificial Intelligence and Operations Research: Challenges and Oppurtunities in Planning and Scheduling. The Knowledge Engineering Review 15, 1–10 (2000)

    Article  Google Scholar 

  10. Vossen, T., Michael, B., Lotem, A., Nau, D.: On the Use of Integer Programming Models in AI Planning. In: Proceedings of Sixteenth International Joint Conf. Artificial Intelligence (IJCAI 1999), Stockholm, Sweden (1999)

    Google Scholar 

  11. Brailsford, S.C., Potts, C.N., Smith, B.M.: Constraint Satisfaction Problems: Algorithms and Applications. EJOR 119, 557–581 (1999)

    Article  MATH  Google Scholar 

  12. Van Hentenryck, P.: Constraint Satisfaction in Logic Programming. MIT Press, Cambridge (1989)

    Google Scholar 

  13. Tsang, E.: Foundations of Constraint Satisfaction. Academic Press, London (1993)

    Google Scholar 

  14. Beringer, H., De Backer, B.: Logic Programming: Formal Methods and Practical Applications, Studies in Computer Science and Artificial Intelligence. In: Beirle, C., Plumer, L. (eds.) Combinatorial Problem Solving in Constraint Logic Programming with Cooperating Solvers. Elsevier Inc., Amsterdam (1995)

    Google Scholar 

  15. Kirkpatrick, S., Gelatt Jr, C.D., Vecchi, M.P.: Optimization by Simulated Annealing. Science 220, 671–680 (1983)

    Article  MathSciNet  Google Scholar 

  16. Glover, F.: Tabu Search-Part I. ORSA Journal on Computing 1, 190–206 (1989)

    MATH  MathSciNet  Google Scholar 

  17. Holland, J.H.: Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  18. Sampson, S.: October Newsletter On-Line Posting, Newsgroup SOMA.byu.edu, October 1 (1997)

    Google Scholar 

  19. Ozkarahan, I.: A Scheduling Model for Hospital Residents. Journal of Medical Systems 18, 261–265 (1994)

    Article  Google Scholar 

  20. Sherali, H.D., Ramahi, M.H., Saifee, Q.J.: Hospital Resident Scheduling Problem. Production Planning and Control 13, 220–233 (2002)

    Article  Google Scholar 

  21. Seitman, D.T.: A Recursive Computer Program to Compute the Daily on-call Assignments for a Medical Department. In: Proceedings of the Annual Conference on Engineering in Medicine and Biology, pp. 1269–1270 (1990)

    Google Scholar 

  22. Haralick, R.M., Elliot, G.L.: Increasing the Efficiency for Constraint Satisfaction Problems. Artificial Intelligence 14, 263–313 (1989)

    Article  Google Scholar 

  23. ILOG.: ILOG OPL Studio 3.5 Language Manual. Gentilly France (2001)

    Google Scholar 

  24. Van Hentenryck, P., Michel, L.: OPL Script: Composing and Controlling Models. In: Apt, K.R., Kakas, A.C., Monfroy, E., Rossi, F. (eds.) Compulog Net WS 1999. LNCS (LNAI), vol. 1865, p. 75. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  25. Baker, K.R.: Introduction to Sequencing and Scheduling. John Wiley, New York (1974)

    Google Scholar 

  26. Morton, T.E., Pentico, D.W. (eds.): Heuristic Scheduling Systems: With Applications to Applications to Production Systems and Project Management. John Wiley & Sons Inc., Canada (1993)

    Google Scholar 

  27. Du, J., Leung, J.Y.T.: Minimizing Total Tardiness On One Machine Is NP-Hard. Mathematics of Operations Research 15, 483–495 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  28. Fry, T.D., Vicens, L., Macleod, K., Fernandez, S.: A Heuristic Solution Procedure to Minimize T on A Single Machine. Journal of the Operational Research Society 40, 293–297 (1989)

    MATH  Google Scholar 

  29. Panwalkar, S.S., Smith, M.L., Koulamas, C.P.: A Heuristic for the Single Machine Tardiness Problem. European Journal of Operational Research 70, 304–310 (1993)

    Article  MATH  Google Scholar 

  30. Potts, C.N., Van Wassenhove, L.N.: A Decomposition Algorithms for the Single Machine Total Tardiness Problem. Operations Research Letters 11, 177–181 (1982)

    Article  Google Scholar 

  31. Goldberg, J.B.: Operations Research Models for the Deployment of Emergency Services Vehicles. EMS Management Journal 1(1), 20–39 (2004)

    Google Scholar 

  32. Marianov, V., ReVelle, C.: Siting Emergency Services. In: Drezner, Z. (ed.) Facility location, pp. 199–223. Springer, Berlin (1995)

    Google Scholar 

  33. Narasimhan, R.: Goal Programming in a Fuzzy Environment. Decision Science 11, 325–336 (1980)

    Article  MathSciNet  Google Scholar 

  34. Hogan, K., ReVelle, C.: Concepts and Applications of Backup Coverage. Management Science 32, 1434–1444 (1986)

    Article  Google Scholar 

  35. Pirkul, H., Schilling, D.: The Maximal Covering Location Problem with Capacities on Total Workload. Management Science 37, 233–248 (1991)

    Article  MATH  Google Scholar 

  36. Zadeh, L.A.: Fuzzy Sets. Information and Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  37. Charnes, A., Cooper, W.W.: Goal Programming and Multiple Objective Optimizations. European Journal of Operational Research 1, 39–54 (1977)

    Article  MATH  MathSciNet  Google Scholar 

  38. Hannan, E.L.: Some Further Comments on Fuzzy Priorities. Decision Science 13, 337–339 (1981)

    Article  Google Scholar 

  39. Tiwari, R.N., Dharmar, S., Rao, J.R.: Priority Structure in Fuzzy Goal Programming. Fuzzy Sets and Systems 19, 251–259 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  40. Tiwari, R.N., Dharmar, S., Rao, J.R.: Fuzzy Goal Programming-an Additive Method. Fuzzy Sets and Systems 24, 27–34 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  41. Zimmermann, H.-J.: Fuzzy programming and linear programming with several objective function. Fuzzy Sets and Systems 1, 45–55 (1978)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Industrial Engineering Department, Dokuz Eylul University, 35100, Izmir, Turkey

    Irem Ozkarahan, Seyda Topaloglu, Ceyhun Araz, Bilge Bilgen & Hasan Selim

Authors
  1. Irem Ozkarahan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seyda Topaloglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ceyhun Araz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bilge Bilgen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hasan Selim
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dokuz Eylül University, lzmir, Turkey

    Tatyana Yakhno

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ozkarahan, I., Topaloglu, S., Araz, C., Bilgen, B., Selim, H. (2004). Integrating AI and OR: An Industrial Engineering Perspective. In: Yakhno, T. (eds) Advances in Information Systems. ADVIS 2004. Lecture Notes in Computer Science, vol 3261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30198-1_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30198-1_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23478-4

  • Online ISBN: 978-3-540-30198-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation