EasyLocal++ is an object-oriented framework that can be used as a general tool for the development of local search algorithms in C++. The basic idea of EasyLocal++ is to capture the essential features of most local search metaheuristics, and their possible compositions. This allows the user to address the design and implementation issues of new local search heuristics in a more principled way. Furthermore, the framework can easily be customized by an expert user allowing the development of new metaheuristics, and its architecture fully supports the reuse of code. EasyLocal++ relies on a few ”Design Patterns”, which are abstract structures of classes, commonly present in object-oriented systems, that have been precisely identified and classified. The framework is basically based on two of them, namely the ”Template Method”, to specify and implement the invariant parts of various search algorithms, and the ”Strategy Method”, for the communication between the main solver and its component classes. The architecture of the framework is composed of a set of cooperating classes, which belong to five main categories, and are organized in a hierarchy of abstraction levels. Each layer of the hierarchy relies on the services supplied by lower levels and provides a set of more abstract operations.

References in zbMATH (referenced in 30 articles )

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  1. Belin, Bruno; Christie, Marc; Truchet, Charlotte: Interactive design of sustainable cities with a distributed local search solver (2014)
  2. Ceschia, Sara; Di Gaspero, Luca; Schaerf, Andrea: The generalized balanced academic curriculum problem with heterogeneous classes (2014)
  3. Ceschia, Sara; Di Gaspero, Luca; Schaerf, Andrea: Design, engineering, and experimental analysis of a simulated annealing approach to the post-enrolment course timetabling problem (2012)
  4. Chiarandini, Marco; Di Gaspero, Luca; Gualandi, Stefano; Schaerf, Andrea: The balanced academic curriculum problem revisited (2012)
  5. Parejo, José Antonio; Ruiz-Cortés, Antonio; Lozano, Sebastián; Fernandez, Pablo: Metaheuristic optimization frameworks: a survey and benchmarking (2012)
  6. Benoist, Thierry; Estellon, Bertrand; Gardi, Frédéric; Megel, Romain; Nouioua, Karim: LocalSolver 1.x: A black-box local-search solver for 0-1 programming (2011)
  7. Ceschia, Sara; Di Gaspero, Luca; Schaerf, Andrea: Tabu search techniques for the heterogeneous vehicle routing problem with time windows and carrier-dependent costs (2011)
  8. Ceschia, Sara; Schaerf, Andrea: Local search and lower bounds for the patient admission scheduling problem (2011)
  9. di Gaspero, Luca; di Tollo, Giacomo; Roli, Andrea; Schaerf, Andrea: Hybrid metaheuristics for constrained portfolio selection problems (2011)
  10. Qu, R.; Burke, E.K.; McCollum, B.; Merlot, L.T.G.; Lee, S.Y.: A survey of search methodologies and automated system development for examination timetabling (2009)
  11. Di Gaspero, Luca; Roli, Andrea: Stochastic local search for large-scale instances of the haplotype inference problem by pure parsimony (2008)
  12. di Tollo, Giacomo; Roli, Andrea: Metaheuristics for the portfolio selection problem (2008)
  13. Cadoli, Marco; Mancini, Toni: Combining relational algebra, SQL, constraint modelling, and local search (2007)
  14. Di Gaspero, Luca; di Tollo, Giacomo; Roli, Andrea; Schaerf, Andrea: Hybrid local search for constrained financial portfolio selection problems (2007)
  15. Di Gaspero, Luca; Gärtner, Johannes; Kortsarz, Guy; Musliu, Nysret; Schaerf, Andrea; Slany, Wolfgang: The minimum shift design problem (2007)
  16. Gaspero, Luca Di; Schaerf, Andrea: A composite-neighborhood tabu search approach to the traveling tournament problem (2007)
  17. Lau, Hoong Chuin; Wan, Wee Chong; Halim, Steven; Toh, Kaiyang: A software framework for fast prototyping of meta-heuristics hybridization (2007)
  18. Chiarandini, Marco; Birattari, Mauro; Socha, Krzysztof; Rossi-Doria, Olivia: An effective hybrid algorithm for university course timetabling (2006)
  19. Di Gaspero, Luca; Schaerf, Andrea: Neighborhood portfolio approach for local search applied to timetabling problems (2006)
  20. Melab, N.; Cahon, S.; Talbi, E-G.: Grid computing for parallel bioinspired algorithms (2006)

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