Skip to main content
Springer Nature Link
Log in

AEGIS—attribute experimentation guiding improvement searches

Offline Framework

  • Published:
Journal of Heuristics Aims and scope Submit manuscript

Abstract

The development of a quality heuristic is a challenging undertaking. While some work has been done to link solution quality and problem inputs, relatively little has been done to methodically address that linkage. This research, a meta-heuristic framework called AEGIS, is an initial attempt to integrate problem characteristics into the solution process itself. As the name implies, the goal is to provide guidance to the solution process, through a well-defined learning process. By utilizing statistical techniques and concepts, this study will demonstrate how such knowledge may be used to drive the function of the algorithm.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Amini, M., Racer, M.: A rigorous computational comparison of alternative solution methodologies for the generalized assignment problem. Manag. Sci. 40, 868–890 (1994)

    Article  MATH  Google Scholar 

  • Cox, D.R., Hinkley, D.V.: Theoretical Statistics. Chapman Hall, New York (1979)

    Google Scholar 

  • Eigen, M., Winkler, R.: Laws of the Game. Harper Collins, New York (1983)

    Google Scholar 

  • Glover, F., Laguna, M.: Tabu Search. Kluwer Academic, Dordrecht (1997)

    MATH  Google Scholar 

  • Glover, F., Laguna, M.: Integrating target analysis, tabu search for improving scheduling systems. Expert Syst. Appl. 6, 287–297 (1993)

    Article  Google Scholar 

  • Golden, B.L., Stewart, W.R.: Empirical analysis of heuristics. In: Lawler, E., Lenstra, J.K., Rinnooy Kan, A., Shmoys, D. (eds.) The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization, pp. 207–249. Wiley, New York (1985)

    Google Scholar 

  • Hooker, J.N.: Needed: an empirical science of algorithms. Oper. Res. 42(2), 201–212 (1994)

    Article  MATH  Google Scholar 

  • Lovgren, R.H.: Mixed model assembly line sequencing. Ph.D. Thesis, Management Science Department, University of Tennessee-Knoxville, Knoxville, TN (1996)

  • Lovgren, R.H., Racer, M.: AEGIS I —attribute experimentation guiding improvement searches: Inline framework (2008, in preparation for submission)

  • Luce, R.D., Raiffa, H.: Games and decisions: introduction, critical survey. Dover, New York (1989)

    Google Scholar 

  • McGeoch, C.C.: Experimental analysis of algorithms. Ph.D. Thesis, CMU-CS-87-124, Computer Science Department, Carnegie-Mellon University, Pittsburgh, PA (1986)

  • Monden, Y.: Toyota Production System: An Integrated Approach to Just-in-Time, 2nd edn. Industrial Engineering and Management Press, Norcross (1993)

    Google Scholar 

  • Sumichrast, R.T., Russell, R.S., Taylor III, B.W.: A comparative analysis of sequencing procedures for mixed-model assembly lines in a just-in-time production system. Int. J. Prod. Res. 30, 199–214 (1992)

    Article  MATH  Google Scholar 

  • Sumichrast, R.T., Russell, R.S.: Evaluating mixed-model assembly line sequencing heuristics for just-in-time production systems. J. Oper. Manag. 9, 371–87 (1990)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Fogelman College of Business & Economics, University of Memphis, Memphis, TN, 38152, USA

    Michael Racer

  2. Industrial and Systems Engineering, University of Memphis, Memphis, TN, 38152, USA

    Robin Lovgren

Authors
  1. Michael Racer
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Robin Lovgren
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Michael Racer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Racer, M., Lovgren, R. AEGIS—attribute experimentation guiding improvement searches. J Heuristics 15, 451–478 (2009). https://doi.org/10.1007/s10732-008-9073-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10732-008-9073-3

Keywords