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A Derivative-Free Filter Driven Multistart Technique for Global Optimization

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Computational Science and Its Applications – ICCSA 2012 (ICCSA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7335))

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Abstract

A stochastic global optimization method based on a multistart strategy and a derivative-free filter local search for general constrained optimization is presented and analyzed. In the local search procedure, approximate descent directions for the constraint violation or the objective function are used to progress towards the optimal solution. The algorithm is able to locate all the local minima, and consequently, the global minimum of a multi-modal objective function. The performance of the multistart method is analyzed with a set of benchmark problems and a comparison is made with other methods.

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References

  1. Ali, M.M., Gabere, M.N.: A simulated annealing driven multi-start algorithm for bound constrained global optimization. Journal of Computational and Applied Mathematics 233, 2661–2674 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  2. Audet, C., Dennis Jr., J.E.: A pattern search filter method for nonlinear programming without derivatives. SIAM Journal on Optimization 14(4), 980–1010 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  3. Costa, M.F.P., Fernandes, E.M.G.P.: Assessing the potential of interior point barrier filter line search methods: nonmonotone versus monotone approach. Optimization 60(10-11), 1251–1268 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  4. Fletcher, R., Leyffer, S.: Nonlinear programming without a penalty function. Mathematical Programming 91, 239–269 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  5. Hedar, A.R., Fukushima, M.: Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization. Journal of Global Optimization 35, 521–549 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  6. Lagaris, I.E., Tsoulos, I.G.: Stopping rules for box-constrained stochastic global optimization. Applied Mathematics and Computation 197, 622–632 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  7. Marti, R.: Multi-start methods. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics, pp. 355–368. Kluwer, Dordrecht (2003)

    Google Scholar 

  8. Rocha, A.M.A.C., Fernandes, E.M.G.P.: Mutation-Based Artificial Fish Swarm Algorithm for Bound Constrained Global Optimization. In: Numerical Analysis and Applied Mathematics ICNAAM 2011. AIP Conf. Proc., vol. 1389, pp. 751–754 (2011)

    Google Scholar 

  9. Tsoulos, I.G., Lagaris, I.E.: MinFinder: Locating all the local minima of a function. Computer Physics Communications 174, 166–179 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  10. Tu, W., Mayne, R.W.: Studies of multi-start clustering for global optimization. International Journal for Numerical Methods in Engineering 53(9), 2239–2252 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  11. Voglis, C., Lagaris, I.E.: Towards ”Ideal Multistart”. A stochastic approach for locating the minima of a continuous function inside a bounded domain. Applied Mathematics and Computation 213, 1404–1415 (2009)

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. ESTiG, Polytechnic Institute of Bragança, 5301-857, Bragança, Portugal

    Florbela P. Fernandes

  2. Department of Mathematics and Applications, University of Minho, 4800-058, Guimarães, Portugal

    M. Fernanda P. Costa

  3. Mathematics R&D Centre, University of Minho, 4710-057, Braga, Portugal

    Florbela P. Fernandes & M. Fernanda P. Costa

  4. Algoritmi R&D Centre, University of Minho, 4710-057, Braga, Portugal

    Edite M. G. P. Fernandes

Authors
  1. Florbela P. Fernandes
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  2. M. Fernanda P. Costa
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  3. Edite M. G. P. Fernandes
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Editor information

Editors and Affiliations

  1. Laboratory of Urban and Territorial Systems, University of Basilicata, 10, Viale dell’Ateneo Lucano, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli 1, 06123, Perugia, Italy

    Osvaldo Gervasi

  3. Department of Cyber Security Science, Federal University of Technology, Gidan Kwano Campus, Minna, Nigeria

    Sanjay Misra

  4. Faculty of Engineering, Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Rua Sao Francisco Xavier, 524, 50. andar, sala 5145-F, Maracana, 20.550-013, Rio de Janeiro, RJ, Brazil

    Nadia Nedjah

  5. Department of Production and Systems, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

  6. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

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© 2012 Springer-Verlag Berlin Heidelberg

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Fernandes, F.P., Costa, M.F.P., Fernandes, E.M.G.P. (2012). A Derivative-Free Filter Driven Multistart Technique for Global Optimization. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31137-6_8

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  • DOI: https://doi.org/10.1007/978-3-642-31137-6_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31136-9

  • Online ISBN: 978-3-642-31137-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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