METSlib

The METSlib QAP solver is a Tabu Search solver for the quadratic assignment problem, a combinatorial optimization problem that arises in many applicative cases. It can be used to find optimal locations for a set of facilities while minimizing the cost of moving commodities between them, to optimize the placement of components on a circuit board, and for many other applications. This software is based on the METSlib framework. (Source: http://freecode.com/)


References in zbMATH (referenced in 35 articles , 1 standard article )

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  1. Gu, Hanyu; Zhang, Yefei; Zinder, Yakov: An efficient optimisation procedure for the workforce scheduling and routing problem: Lagrangian relaxation and iterated local search (2022)
  2. Roohnavazfar, Mina; Pasandideh, Seyed Hamid Reza; Tadei, Roberto: A hybrid algorithm for the vehicle routing problem with and/or precedence constraints and time windows (2022)
  3. Allahyari, Somayeh; Yaghoubi, Saeed; Van Woensel, Tom: The secure time-dependent vehicle routing problem with uncertain demands (2021)
  4. Hesam Sadati, Mir Ehsan; Çatay, Bülent; Aksen, Deniz: An efficient variable neighborhood search with tabu shaking for a class of multi-depot vehicle routing problems (2021)
  5. Máximo, Vinícius R.; Nascimento, Mariá C. V.: A hybrid adaptive iterated local search with diversification control to the capacitated vehicle routing problem (2021)
  6. Schryen, Guido: Parallel computational optimization in operations research: a new integrative framework, literature review and research directions (2020)
  7. Kramer, Arthur; Subramanian, Anand: A unified heuristic and an annotated bibliography for a large class of earliness-tardiness scheduling problems (2019)
  8. Penna, Puca Huachi Vaz; Subramanian, Anand; Ochi, Luiz Satoru; Vidal, Thibaut; Prins, Christian: A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet (2019)
  9. Pessoa, Artur; Sadykov, Ruslan; Uchoa, Eduardo: Enhanced branch-cut-and-price algorithm for heterogeneous fleet vehicle routing problems (2018)
  10. Stodola, Petr: Using metaheuristics on the multi-depot vehicle routing problem with modified optimization criterion (2018)
  11. Chen, Yujie; Cowling, Peter; Polack, Fiona; Remde, Stephen; Mourdjis, Philip: Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system (2017)
  12. Galligari, Alessandro; Maischberger, Mirko; Schoen, Fabio: Local search heuristics for the zone planning problem (2017)
  13. Ma, Fuda; Hao, Jin-Kao; Wang, Yang: An effective iterated tabu search for the maximum bisection problem (2017)
  14. Paraskevopoulos, Dimitris C.; Laporte, Gilbert; Repoussis, Panagiotis P.; Tarantilis, Christos D.: Resource constrained routing and scheduling: review and research prospects (2017)
  15. Schneider, Michael; Schwahn, Fabian; Vigo, Daniele: Designing granular solution methods for routing problems with time windows (2017)
  16. Silvestrin, Paulo Vitor; Ritt, Marcus: An iterated tabu search for the multi-compartment vehicle routing problem (2017)
  17. Bae, Heechul; Moon, Ilkyeong: Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles (2016)
  18. Doppstadt, C.; Koberstein, A.; Vigo, D.: The hybrid electric vehicle-traveling salesman problem (2016)
  19. Li, Jian; Li, Yang; Pardalos, Panos M.: Multi-depot vehicle routing problem with time windows under shared depot resources (2016)
  20. Cherif-Khettaf, Wahiba Ramdane; Rachid, Mais Haj; Bloch, Christelle; Chatonnay, Pascal: New notation and classification scheme for vehicle routing problems (2015)

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