POPMUSIC -- partial optimization metaheuristic under special intensification conditions. This article introduces POPMUSIC, a meta-heuristic that has been successfully applied to various combinatorial optimization problems. This metaheuristic is especially useful for designing heuristic methods for large combinatorial problems that can be partially optimized. The basic idea is to optimize sub-parts of solutions until a local optimum is reached. Implementations of the technique to large centroid clustering and to the problem of balancing mechanical parts are shown to be very efficient.

References in zbMATH (referenced in 24 articles , 2 standard articles )

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  1. Lalla-Ruiz, Eduardo; Voß, Stefan: A POPMUSIC approach for the multi-depot cumulative capacitated vehicle routing problem (2020)
  2. Nishi, Tatsushi; Okura, Tatsuya; Lalla-Ruiz, Eduardo; Voß, Stefan: A dynamic programming-based matheuristic for the dynamic berth allocation problem (2020)
  3. Taillard, Éric D.; Helsgaun, Keld: POPMUSIC for the travelling salesman problem (2019)
  4. Doi, Tsubasa; Nishi, Tatsushi; Voß, Stefan: Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time (2018)
  5. Lalla-Ruiz, Eduardo; Voß, Stefan; Expósito-Izquierdo, Christopher; Melián-Batista, Belén; Moreno-Vega, J. Marcos: A POPMUSIC-based approach for the berth allocation problem under time-dependent limitations (2017)
  6. Lehouillier, Thibault; Omer, Jérémy; Soumis, François; Desaulniers, Guy: Two decomposition algorithms for solving a minimum weight maximum clique model for the air conflict resolution problem (2017)
  7. Paes, Frederico Galaxe; Pessoa, Artur Alves; Vidal, Thibaut: A hybrid genetic algorithm with decomposition phases for the unequal area facility layout problem (2017)
  8. Salmani, Mohammad Hassan; Eshghi, Kourosh: A metaheuristic algorithm based on chemotherapy science: CSA (2017)
  9. Schneider, Michael; Drexl, Michael: A survey of the standard location-routing problem (2017)
  10. Schneider, Michael; Schwahn, Fabian; Vigo, Daniele: Designing granular solution methods for routing problems with time windows (2017)
  11. Lalla-Ruiz, Eduardo; Voß, Stefan: POPMUSIC as a matheuristic for the berth allocation problem (2016)
  12. Talbi, El-Ghazali: Combining metaheuristics with mathematical programming, constraint programming and machine learning (2016)
  13. Raidl, Günther R.: Decomposition based hybrid metaheuristics (2015)
  14. Caserta, Marco; Voß, Stefan: A hybrid algorithm for the DNA sequencing problem (2014)
  15. Rabello, Rômulo Louzada; Mauri, Geraldo Regis; Ribeiro, Glaydston Mattos; Lorena, Luiz Antonio Nogueira: A clustering search metaheuristic for the point-feature cartographic label placement problem (2014)
  16. Talbi, El-Ghazali: Combining metaheuristics with mathematical programming, constraint programming and machine learning (2013)
  17. Ribeiro, Glaydston M.; Mauri, Geraldo R.; Lorena, Luiz Antonio N.: A Lagrangean decomposition for the maximum independent set problem applied to map labeling (2011)
  18. Mauri, Geraldo R.; Ribeiro, Glaydston M.; Lorena, Luiz A. N.: A new mathematical model and a Lagrangean decomposition for the point-feature cartographic label placement problem (2010)
  19. Alvim, Adriana C. F.; Taillard, Éric D.: POPMUSIC for the point feature label placement problem (2009)
  20. Hu, Bin; Leitner, Markus; Raidl, Günther R.: Combining variable neighborhood search with integer linear programming for the generalized minimum spanning tree problem (2008)

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