GLOB

GLOB -- a new VNS-based software for global optimization We describe an application of Variable Neighbourhood Search (VNS) methodology to continuous global optimization problems with box constraints. A general VNS algorithm is implemented within the software package GLOB. The tests are performed on some standard test functions and on a class of NP-hard global optimization problems arising in practice. The computational results show the potential of the new software


References in zbMATH (referenced in 40 articles , 1 standard article )

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  1. Brusco, Michael J.; Steinley, Douglas: A variable neighborhood search heuristic for nonnegative matrix factorization with application to microarray data (2022)
  2. Cavero, Sergio; Pardo, Eduardo G.; Duarte, Abraham: A general variable neighborhood search for the cyclic antibandwidth problem (2022)
  3. Cheimanoff, Nicolas; Fontane, Frédéric; Kitri, Mohamed Nour; Tchernev, Nikolay: Exact and heuristic methods for the integrated berth allocation and specific time-invariant quay crane assignment problems (2022)
  4. Hedar, Abdel-Rahman; Deabes, Wael; Amin, Hesham H.; Almaraashi, Majid; Fukushima, Masao: Global sensing search for nonlinear global optimization (2022)
  5. Dražić, Milan: Influence of a neighborhood shape on the efficiency of continuous variable neighborhood search (2020)
  6. Pei, Jun; Dražić, Zorica; Dražić, Milan; Mladenović, Nenad; Pardalos, Panos M.: Continuous variable neighborhood search (C-VNS) for solving systems of nonlinear equations (2019)
  7. Carrizosa, Emilio; Guerrero, Vanesa; Romero Morales, Dolores: Visualizing data as objects by DC (difference of convex) optimization (2018)
  8. Gaudioso, Manlio; Giallombardo, Giovanni; Miglionico, Giovanna: Minimizing piecewise-concave functions over polyhedra (2018)
  9. Gonçalves-E-Silva, Kayo; Aloise, Daniel; Xavier-De-Souza, Samuel; Mladenović, Nenad: Less is more: simplified Nelder-Mead method for large unconstrained optimization (2018)
  10. Drezner, Zvi; Salhi, Said: Incorporating neighborhood reduction for the solution of the planar (p)-median problem (2017)
  11. Hansen, Pierre; Mladenović, Nenad; Todosijević, Raca; Hanafi, Saïd: Variable neighborhood search: basics and variants (2017)
  12. Locatelli, Marco; Schoen, Fabio: Global optimization based on local searches (2016)
  13. Sicilia, Juan Antonio; Quemada, Carlos; Royo, Beatriz; Escuín, David: An optimization algorithm for solving the rich vehicle routing problem based on variable neighborhood search and tabu search metaheuristics (2016)
  14. Alonso-Ayuso, Antonio; Escudero, Laureano F.; Martín-Campo, F. Javier; Mladenović, Nenad: A VNS metaheuristic for solving the aircraft conflict detection and resolution problem by performing turn changes (2015)
  15. Drezner, Zvi; Brimberg, Jack; Mladenović, Nenad; Salhi, Said: New heuristic algorithms for solving the planar (p)-median problem (2015)
  16. Kaabi, Hadhami; Jabeur, Khaled; Enneifar, Lamia: Learning criteria weights with TOPSIS method and continuous VNS for multi-criteria inventory classification (2015)
  17. Carrizosa, Emilio; Jocković, Jelena; Ramírez-Cobo, Pepa: A global optimisation approach for parameter estimation of a mixture of double Pareto lognormal and lognormal distributions (2014)
  18. Carrizosa, Emilio; Martín-Barragán, Belén; Morales, Dolores Romero: A nested heuristic for parameter tuning in support vector machines (2014)
  19. Djogatović, Marko S.; Stanojević, Milorad J.; Mladenović, Nenad: A variable neighborhood search particle filter for bearings-only target tracking (2014)
  20. Kocatürk, Fatih; Özpeynirci, Özgür: Variable neighborhood search for the pharmacy duty scheduling problem (2014)

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