IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v115y2002i1d10.1023_a1019633214895.html
   My bibliography  Save this article

Analysis of Static Simulated Annealing Algorithms

Author

Listed:
  • J.E. Orosz

    (Wright–Patterson Air Force Base)

  • S.H. Jacobson

    (University of Illinois)

Abstract

Generalized hill climbing (GHC) algorithms provide a framework for modeling local search algorithms to address intractable discrete optimization problems. This paper introduces a measure for determining the expected number of iterations to visit a predetermined objective function level, given that an inferior objective function level has been reached in a finite number of iterations. A variation of simulated annealing (SA), termed static simulated annealing (S2A), is analyzed using this measure. S2A uses a fixed cooling schedule during the algorithm execution. Though S2A is probably nonconvergent, its finite-time performance can be assessed using the finite-time performance measure defined in this paper.

Suggested Citation

  • J.E. Orosz & S.H. Jacobson, 2002. "Analysis of Static Simulated Annealing Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 115(1), pages 165-182, October.
    • Handle: RePEc:spr:joptap:v:115:y:2002:i:1:d:10.1023_a:1019633214895
    DOI: 10.1023/A:1019633214895
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1023/A:1019633214895
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1023/A:1019633214895?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bruce Hajek, 1988. "Cooling Schedules for Optimal Annealing," Mathematics of Operations Research, INFORMS, vol. 13(2), pages 311-329, May.
    2. Mark Fleischer & Sheldon H. Jacobson, 1999. "Information Theory and the Finite-Time Behavior of the Simulated Annealing Algorithm: Experimental Results," INFORMS Journal on Computing, INFORMS, vol. 11(1), pages 35-43, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    2. Sheldon H. Jacobson & Shane N. Hall & Laura A. McLay & Jeffrey E. Orosz, 2005. "Performance Analysis of Cyclical Simulated Annealing Algorithms," Methodology and Computing in Applied Probability, Springer, vol. 7(2), pages 183-201, June.
    3. Zahra Pooranian & Mohammad Shojafar & Jemal H. Abawajy & Ajith Abraham, 2015. "An efficient meta-heuristic algorithm for grid computing," Journal of Combinatorial Optimization, Springer, vol. 30(3), pages 413-434, October.
    4. Alexander Nikolaev & Sheldon Jacobson & Shane Hall & Darrall Henderson, 2011. "A framework for analyzing sub-optimal performance of local search algorithms," Computational Optimization and Applications, Springer, vol. 49(3), pages 407-433, July.
    5. Franzin, Alberto & Stützle, Thomas, 2023. "A landscape-based analysis of fixed temperature and simulated annealing," European Journal of Operational Research, Elsevier, vol. 304(2), pages 395-410.
    6. Marc Robini & Pierre-Jean Reissman, 2013. "From simulated annealing to stochastic continuation: a new trend in combinatorial optimization," Journal of Global Optimization, Springer, vol. 56(1), pages 185-215, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sheldon H. Jacobson & Shane N. Hall & Laura A. McLay & Jeffrey E. Orosz, 2005. "Performance Analysis of Cyclical Simulated Annealing Algorithms," Methodology and Computing in Applied Probability, Springer, vol. 7(2), pages 183-201, June.
    2. C. P. Stephens & W. Baritompa, 1998. "Global Optimization Requires Global Information," Journal of Optimization Theory and Applications, Springer, vol. 96(3), pages 575-588, March.
    3. Stoica, R.S. & Gregori, P. & Mateu, J., 2005. "Simulated annealing and object point processes: Tools for analysis of spatial patterns," Stochastic Processes and their Applications, Elsevier, vol. 115(11), pages 1860-1882, November.
    4. George Kapetanios, 2005. "Variable Selection using Non-Standard Optimisation of Information Criteria," Working Papers 533, Queen Mary University of London, School of Economics and Finance.
    5. Souvik Das & Ashwin Aravind & Ashish Cherukuri & Debasish Chatterjee, 2022. "Near-optimal solutions of convex semi-infinite programs via targeted sampling," Annals of Operations Research, Springer, vol. 318(1), pages 129-146, November.
    6. Pirlot, Marc, 1996. "General local search methods," European Journal of Operational Research, Elsevier, vol. 92(3), pages 493-511, August.
    7. Steinhofel, K. & Albrecht, A. & Wong, C. K., 1999. "Two simulated annealing-based heuristics for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 118(3), pages 524-548, November.
    8. Löwe, Matthias, 1997. "On the invariant measure of non-reversible simulated annealing," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 189-193, December.
    9. Miclo, Laurent, 1995. "Remarques sur l'ergodicité des algorithmes de recuit simulé sur un graphe," Stochastic Processes and their Applications, Elsevier, vol. 58(2), pages 329-360, August.
    10. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
    11. Antonio Jiménez-Martín & Alfonso Mateos & Josefa Z. Hernández, 2021. "Aluminium Parts Casting Scheduling Based on Simulated Annealing," Mathematics, MDPI, vol. 9(7), pages 1-18, March.
    12. Van Buer, Michael G. & Woodruff, David L. & Olson, Rick T., 1999. "Solving the medium newspaper production/distribution problem," European Journal of Operational Research, Elsevier, vol. 115(2), pages 237-253, June.
    13. Zhang Lihao & Ye Zeyang & Deng Yuefan, 2019. "Parallel MCMC methods for global optimization," Monte Carlo Methods and Applications, De Gruyter, vol. 25(3), pages 227-237, September.
    14. Yiyo Kuo, 2014. "Design method using hybrid of line-type and circular-type routes for transit network system optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 600-613, July.
    15. Broekmeulen, Rob A. C. M. & van Weert, Arjen & Saedt, Anton P. H., 2002. "Comparing three alternative optimisation methods for the treatment planning of bulbs," Agricultural Systems, Elsevier, vol. 72(1), pages 59-71, April.
    16. F. R. B. Cruz & A. R. Duarte & G. L. Souza, 2018. "Multi-objective performance improvements of general finite single-server queueing networks," Journal of Heuristics, Springer, vol. 24(5), pages 757-781, October.
    17. Rodriguez-Tello, Eduardo & Hao, Jin-Kao & Torres-Jimenez, Jose, 2008. "An improved simulated annealing algorithm for bandwidth minimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1319-1335, March.
    18. Doole, Graeme J., 2007. "A primer on implementing compressed simulated annealing for the optimisation of a constrained simulation model in Microsoft Excel," Working Papers 7420, University of Western Australia, School of Agricultural and Resource Economics.
    19. Sam Hui & Eric Bradlow, 2012. "Bayesian multi-resolution spatial analysis with applications to marketing," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 419-452, December.
    20. Zhao, Fang & Zeng, Xiaogang, 2008. "Optimization of transit route network, vehicle headways and timetables for large-scale transit networks," European Journal of Operational Research, Elsevier, vol. 186(2), pages 841-855, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joptap:v:115:y:2002:i:1:d:10.1023_a:1019633214895. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.