IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v205y2010i3p507-521.html
   My bibliography  Save this article

Speeding up continuous GRASP

Author

Listed:
  • Hirsch, M.J.
  • Pardalos, P.M.
  • Resende, M.G.C.

Abstract

Continuous GRASP (C-GRASP) is a stochastic local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints (Hirsch et al., 2007). Like a greedy randomized adaptive search procedure (GRASP), a C-GRASP is a multi-start procedure where a starting solution for local improvement is constructed in a greedy randomized fashion. In this paper, we describe several improvements that speed up the original C-GRASP and make it more robust. We compare the new C-GRASP with the original version as well as with other algorithms from the recent literature on a set of benchmark multimodal test functions whose global minima are known. Hart's sequential stopping rule (1998) is implemented and C-GRASP is shown to converge on all test problems.

Suggested Citation

  • Hirsch, M.J. & Pardalos, P.M. & Resende, M.G.C., 2010. "Speeding up continuous GRASP," European Journal of Operational Research, Elsevier, vol. 205(3), pages 507-521, September.
    • Handle: RePEc:eee:ejores:v:205:y:2010:i:3:p:507-521
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(10)00114-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Hedar, Abdel-Rahman & Fukushima, Masao, 2006. "Tabu Search directed by direct search methods for nonlinear global optimization," European Journal of Operational Research, Elsevier, vol. 170(2), pages 329-349, April.
    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. Ivorra, Benjamin & Mohammadi, Bijan & Manuel Ramos, Angel, 2015. "A multi-layer line search method to improve the initialization of optimization algorithms," European Journal of Operational Research, Elsevier, vol. 247(3), pages 711-720.
    2. Emile Glorieux & Bo Svensson & Fredrik Danielsson & Bengt Lennartson, 2017. "Constructive cooperative coevolution for large-scale global optimisation," Journal of Heuristics, Springer, vol. 23(6), pages 449-469, December.
    3. Morales-Enciso, Sergio & Branke, Juergen, 2015. "Tracking global optima in dynamic environments with efficient global optimization," European Journal of Operational Research, Elsevier, vol. 242(3), pages 744-755.
    4. Michael J. Hirsch & Daniel E. Schroeder & Alvaro Maggiar & Irina S. Dolinskaya, 2014. "Multi-depot vessel routing problem in a direction dependent wavefield," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 38-57, July.
    5. C. J. Price & M. Reale & B. L. Robertson, 2021. "Oscars-ii: an algorithm for bound constrained global optimization," Journal of Global Optimization, Springer, vol. 79(1), pages 39-57, January.
    6. Kammerdiner, A.R. & Pasiliao, E.L., 2014. "In and out forests on combinatorial landscapes," European Journal of Operational Research, Elsevier, vol. 236(1), pages 78-84.
    7. Tiago Maritan Ugulino Araújo & Lisieux Marie M. S. Andrade & Carlos Magno & Lucídio Anjos Formiga Cabral & Roberto Quirino Nascimento & Cláudio N. Meneses, 2016. "DC-GRASP: directing the search on continuous-GRASP," Journal of Heuristics, Springer, vol. 22(4), pages 365-382, August.
    8. László Pál, 2017. "Empirical study of the improved UNIRANDI local search method," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 929-952, December.
    9. Ricardo Silva & Mauricio Resende & Panos Pardalos, 2014. "Finding multiple roots of a box-constrained system of nonlinear equations with a biased random-key genetic algorithm," Journal of Global Optimization, Springer, vol. 60(2), pages 289-306, October.
    10. R. M. A. Silva & M. G. C. Resende & P. M. Pardalos, 2015. "A Python/C++ library for bound-constrained global optimization using a biased random-key genetic algorithm," Journal of Combinatorial Optimization, Springer, vol. 30(3), pages 710-728, October.

    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. Ivorra, Benjamin & Mohammadi, Bijan & Manuel Ramos, Angel, 2015. "A multi-layer line search method to improve the initialization of optimization algorithms," European Journal of Operational Research, Elsevier, vol. 247(3), pages 711-720.
    2. Schlereth, Christian & Stepanchuk, Tanja & Skiera, Bernd, 2010. "Optimization and analysis of the profitability of tariff structures with two-part tariffs," European Journal of Operational Research, Elsevier, vol. 206(3), pages 691-701, November.
    3. Hvattum, Lars Magnus & Glover, Fred, 2009. "Finding local optima of high-dimensional functions using direct search methods," European Journal of Operational Research, Elsevier, vol. 195(1), pages 31-45, May.
    4. M. Bierlaire & M. Thémans & N. Zufferey, 2010. "A Heuristic for Nonlinear Global Optimization," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 59-70, February.
    5. Chang-Yong Lee & Dongju Lee, 2014. "Determination of initial temperature in fast simulated annealing," Computational Optimization and Applications, Springer, vol. 58(2), pages 503-522, June.
    6. S.-C. Horng & S.-Y. Lin, 2009. "Ordinal Optimization of G/G/1/K Polling Systems with k-Limited Service Discipline," Journal of Optimization Theory and Applications, Springer, vol. 140(2), pages 213-231, February.
    7. Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2011. "A hybrid shuffled complex evolution approach with pattern search for unconstrained optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1901-1909.
    8. Tiago Maritan Ugulino Araújo & Lisieux Marie M. S. Andrade & Carlos Magno & Lucídio Anjos Formiga Cabral & Roberto Quirino Nascimento & Cláudio N. Meneses, 2016. "DC-GRASP: directing the search on continuous-GRASP," Journal of Heuristics, Springer, vol. 22(4), pages 365-382, August.
    9. Naanaa, Anis, 2015. "Fast chaotic optimization algorithm based on spatiotemporal maps for global optimization," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 402-411.
    10. Piotrowski, Adam P. & Napiorkowski, Jaroslaw J. & Kiczko, Adam, 2012. "Differential Evolution algorithm with Separated Groups for multi-dimensional optimization problems," European Journal of Operational Research, Elsevier, vol. 216(1), pages 33-46.
    11. Hwang Yi & Mi-Jin Kim & Yuri Kim & Sun-Sook Kim & Kyu-In Lee, 2019. "Rapid Simulation of Optimally Responsive Façade during Schematic Design Phases: Use of a New Hybrid Metaheuristic Algorithm," Sustainability, MDPI, vol. 11(9), pages 1-28, May.
    12. M. Gaviano & D. Lera & A. Steri, 2010. "A local search method for continuous global optimization," Journal of Global Optimization, Springer, vol. 48(1), pages 73-85, September.
    13. A. Custódio & J. Madeira, 2015. "GLODS: Global and Local Optimization using Direct Search," Journal of Global Optimization, Springer, vol. 62(1), pages 1-28, May.
    14. Kazancoglu, Yigit & Sagnak, Muhittin & Mangla, Sachin Kumar & Sezer, Muruvvet Deniz & Pala, Melisa Ozbiltekin, 2021. "A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    15. Abraham Duarte & Rafael Martí & Fred Glover & Francisco Gortazar, 2011. "Hybrid scatter tabu search for unconstrained global optimization," Annals of Operations Research, Springer, vol. 183(1), pages 95-123, March.
    16. Yin, Peng-Yeng & Glover, Fred & Laguna, Manuel & Zhu, Jia-Xian, 2010. "Cyber Swarm Algorithms - Improving particle swarm optimization using adaptive memory strategies," European Journal of Operational Research, Elsevier, vol. 201(2), pages 377-389, March.
    17. Fei Wei & Yuping Wang & Hongwei Lin, 2014. "A New Filled Function Method with Two Parameters for Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 163(2), pages 510-527, November.
    18. Gouvêa, Érica J.C. & Regis, Rommel G. & Soterroni, Aline C. & Scarabello, Marluce C. & Ramos, Fernando M., 2016. "Global optimization using q-gradients," European Journal of Operational Research, Elsevier, vol. 251(3), pages 727-738.
    19. Gisela C. V. Ramadas & Edite M. G. P. Fernandes & António M. V. Ramadas & Ana Maria A. C. Rocha & M. Fernanda P. Costa, 2018. "On Metaheuristics for Solving the Parameter Estimation Problem in Dynamic Systems: A Comparative Study," Journal of Optimization, Hindawi, vol. 2018, pages 1-21, 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:eee:ejores:v:205:y:2010:i:3:p:507-521. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.