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General variable neighborhood search for the continuous optimization

Author

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  • Mladenovic, Nenad
  • Drazic, Milan
  • Kovacevic-Vujcic, Vera
  • Cangalovic, Mirjana

Abstract

We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Different neighborhoods and distributions, induced from different metrics are ranked and used to get random points in the shaking step. We also propose VNS for solving constrained optimization problems. The constraints are handled using exterior point penalty functions within an algorithm that combines sequential and exact penalty transformations. The extensive computer analysis that includes the comparison with genetic algorithm and some other approaches on standard test functions are given. With our approach we obtain encouraging results.

Suggested Citation

  • Mladenovic, Nenad & Drazic, Milan & Kovacevic-Vujcic, Vera & Cangalovic, Mirjana, 2008. "General variable neighborhood search for the continuous optimization," European Journal of Operational Research, Elsevier, vol. 191(3), pages 753-770, December.
  • Handle: RePEc:eee:ejores:v:191:y:2008:i:3:p:753-770
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    References listed on IDEAS

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    1. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    2. Brimberg, J. & Urosevic, D. & Mladenovic, N., 2006. "Variable neighborhood search for the vertex weighted k-cardinality tree problem," European Journal of Operational Research, Elsevier, vol. 171(1), pages 74-84, May.
    3. Charles Audet & Jack Brimberg & Pierre Hansen & Sébastien Le Digabel & Nenad Mladenovi'{c}, 2004. "Pooling Problem: Alternate Formulations and Solution Methods," Management Science, INFORMS, vol. 50(6), pages 761-776, June.
    4. Mladenovic, N. & Petrovic, J. & Kovacevic-Vujcic, V. & Cangalovic, M., 2003. "Solving spread spectrum radar polyphase code design problem by tabu search and variable neighbourhood search," European Journal of Operational Research, Elsevier, vol. 151(2), pages 389-399, December.
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    1. repec:spr:annopr:v:240:y:2016:i:1:d:10.1007_s10479-015-2014-2 is not listed on IDEAS
    2. Massimo Spadoni & Luciano Stefanini, 2012. "A Differential Evolution algorithm to deal with box, linear and quadratic-convex constraints for boundary optimization," Journal of Global Optimization, Springer, vol. 52(1), pages 171-192, January.
    3. Carrizosa, Emilio & Olivares-Nadal, Alba V. & Ramírez-Cobo, Pepa, 2013. "Time series interpolation via global optimization of moments fitting," European Journal of Operational Research, Elsevier, vol. 230(1), pages 97-112.
    4. Souza, M.J.F. & Coelho, I.M. & Ribas, S. & Santos, H.G. & Merschmann, L.H.C., 2010. "A hybrid heuristic algorithm for the open-pit-mining operational planning problem," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1041-1051, December.
    5. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.

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