IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v47y2010i2p293-325.html
   My bibliography  Save this article

The oracle penalty method

Author

Listed:
  • Martin Schlüter
  • Matthias Gerdts

Abstract

No abstract is available for this item.

Suggested Citation

  • Martin Schlüter & Matthias Gerdts, 2010. "The oracle penalty method," Journal of Global Optimization, Springer, vol. 47(2), pages 293-325, June.
    • Handle: RePEc:spr:jglopt:v:47:y:2010:i:2:p:293-325
    DOI: 10.1007/s10898-009-9477-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10898-009-9477-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10898-009-9477-0?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. Socha, Krzysztof & Dorigo, Marco, 2008. "Ant colony optimization for continuous domains," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1155-1173, March.
    2. Atidel Ben Hadj-Alouane & James C. Bean, 1997. "A Genetic Algorithm for the Multiple-Choice Integer Program," Operations Research, INFORMS, vol. 45(1), pages 92-101, 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. Maen Z. Kreishan & Ahmed F. Zobaa, 2023. "Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization," Energies, MDPI, vol. 16(10), pages 1-30, May.
    2. Eryang Guo & Yuelin Gao & Chenyang Hu & Jiaojiao Zhang, 2023. "A Hybrid PSO-DE Intelligent Algorithm for Solving Constrained Optimization Problems Based on Feasibility Rules," Mathematics, MDPI, vol. 11(3), pages 1-34, January.
    3. Umesh Balande & Deepti Shrimankar, 2020. "An oracle penalty and modified augmented Lagrangian methods with firefly algorithm for constrained optimization problems," Operational Research, Springer, vol. 20(2), pages 985-1010, June.
    4. J. Gago-Vargas & I. Hartillo & J. Puerto & J. Ucha, 2015. "An improved test set approach to nonlinear integer problems with applications to engineering design," Computational Optimization and Applications, Springer, vol. 62(2), pages 565-588, November.
    5. Teichgraeber, Holger & Brodrick, Philip G. & Brandt, Adam R., 2017. "Optimal design and operations of a flexible oxyfuel natural gas plant," Energy, Elsevier, vol. 141(C), pages 506-518.
    6. Gauri Thakur & Ashok Pal & Nitin Mittal & Asha Rajiv & Rohit Salgotra, 2024. "Slime Mould Algorithm Based on a Gaussian Mutation for Solving Constrained Optimization Problems," Mathematics, MDPI, vol. 12(10), pages 1-37, May.
    7. Nikolaos Ploskas & Nikolaos V. Sahinidis, 2022. "Review and comparison of algorithms and software for mixed-integer derivative-free optimization," Journal of Global Optimization, Springer, vol. 82(3), pages 433-462, March.
    8. Kalyanmoy Deb & Soumil Srivastava, 2012. "A genetic algorithm based augmented Lagrangian method for constrained optimization," Computational Optimization and Applications, Springer, vol. 53(3), pages 869-902, December.
    9. Maen Z. Kreishan & Ahmed F. Zobaa, 2022. "Mixed-Integer Distributed Ant Colony Optimization of Dump Load Allocation with Improved Islanded Microgrid Load Flow," Energies, MDPI, vol. 16(1), pages 1-30, December.
    10. Qiao Zhao & Mounir Mecheri & Thibaut Neveux & Romain Privat & Jean-Noël Jaubert & Yann Le Moullec, 2023. "Search for the Optimal Design of a Supercritical-CO 2 Brayton Power Cycle from a Superstructure-Based Approach Implemented in a Commercial Simulation Software," Energies, MDPI, vol. 16(14), pages 1-31, July.

    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. Amjad Hudaib & Mohammad Khanafseh & Ola Surakhi, 2018. "An Improved Version of K-medoid Algorithm using CRO," Modern Applied Science, Canadian Center of Science and Education, vol. 12(2), pages 116-116, February.
    2. Liao, Tianjun & Stützle, Thomas & Montes de Oca, Marco A. & Dorigo, Marco, 2014. "A unified ant colony optimization algorithm for continuous optimization," European Journal of Operational Research, Elsevier, vol. 234(3), pages 597-609.
    3. Ali Sardar Shahraki & Mohim Tash & Tommaso Caloiero & Ommolbanin Bazrafshan, 2024. "Optimal Allocation of Water Resources Using Agro-Economic Development and Colony Optimization Algorithm," Sustainability, MDPI, vol. 16(13), pages 1-18, July.
    4. Luo, Qifang & Yang, Xiao & Zhou, Yongquan, 2019. "Nature-inspired approach: An enhanced moth swarm algorithm for global optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 159(C), pages 57-92.
    5. Alice E. Smith, 2023. "Note from the Editor," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 711-712, July.
    6. Qiang Yang & Xu Guo & Xu-Dong Gao & Dong-Dong Xu & Zhen-Yu Lu, 2022. "Differential Elite Learning Particle Swarm Optimization for Global Numerical Optimization," Mathematics, MDPI, vol. 10(8), pages 1-32, April.
    7. Jeffrey W. Ohlmann & Barrett W. Thomas, 2007. "A Compressed-Annealing Heuristic for the Traveling Salesman Problem with Time Windows," INFORMS Journal on Computing, INFORMS, vol. 19(1), pages 80-90, February.
    8. Jacob R. Fooks & Kent D. Messer & Maik Kecinski, 2018. "A Cautionary Note on the Use of Benefit Metrics for Cost-Effective Conservation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(4), pages 985-999, December.
    9. Hakan Yılmazer & Selma Ayşe Özel, 2024. "Diverse but Relevant Recommendations with Continuous Ant Colony Optimization," Mathematics, MDPI, vol. 12(16), pages 1-26, August.
    10. Hong, Wei-Chiang, 2010. "Application of chaotic ant swarm optimization in electric load forecasting," Energy Policy, Elsevier, vol. 38(10), pages 5830-5839, October.
    11. Gao, Wei-feng & Huang, Ling-ling & Liu, San-yang & Chan, Felix T.S. & Dai, Cai & Shan, Xian, 2015. "Artificial bee colony algorithm with multiple search strategies," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 269-287.
    12. Ana Maria A. C. Rocha & M. Fernanda P. Costa & Edite M. G. P. Fernandes, 2017. "On a smoothed penalty-based algorithm for global optimization," Journal of Global Optimization, Springer, vol. 69(3), pages 561-585, November.
    13. Li, Yuanmao & Liu, Guixiong & Deng, Wei & Li, Zuyu, 2024. "Comparative study on parameter identification of an electrochemical model for lithium-ion batteries via meta-heuristic methods," Applied Energy, Elsevier, vol. 367(C).
    14. Behzad Ataie-Ashtiani & Hamed Ketabchi, 2011. "Elitist Continuous Ant Colony Optimization Algorithm for Optimal Management of Coastal Aquifers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 165-190, January.
    15. Zhihua Chen & Xuchen Xu & Hongbo Liu, 2023. "The Successive Approximation Genetic Algorithm (SAGA) for Optimization Problems with Single Constraint," Mathematics, MDPI, vol. 11(8), pages 1-26, April.
    16. Jeffrey W. Ohlmann & James C. Bean & Shane G. Henderson, 2004. "Convergence in Probability of Compressed Annealing," Mathematics of Operations Research, INFORMS, vol. 29(4), pages 837-860, November.
    17. Md. Hossain & A. El-shafie, 2013. "Intelligent Systems in Optimizing Reservoir Operation Policy: A Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3387-3407, July.
    18. Warren Liao, T. & Chang, P.C., 2010. "Impacts of forecast, inventory policy, and lead time on supply chain inventory--A numerical study," International Journal of Production Economics, Elsevier, vol. 128(2), pages 527-537, December.
    19. Broderick Crawford & Ricardo Soto & Gino Astorga & José García & Carlos Castro & Fernando Paredes, 2017. "Putting Continuous Metaheuristics to Work in Binary Search Spaces," Complexity, Hindawi, vol. 2017, pages 1-19, May.
    20. Asghar Mahdavi & Mohammad Shiri, 2015. "An augmented Lagrangian ant colony based method for constrained optimization," Computational Optimization and Applications, Springer, vol. 60(1), pages 263-276, January.

    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:jglopt:v:47:y:2010:i:2:p:293-325. 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.