ParaDisEO

In this paper, we present the ParadisEO white-box object-oriented framework dedicated to the reusable design of parallel and distributed metaheuristics (PDM). ParadisEO provides a broad range of features including evolutionary algorithms (EA), local searches (LS), the most common parallel and distributed models and hybridization mechanisms, etc. This high content and utility encourages its use at European level. ParadisEO is based on a clear conceptual separation of the solution methods from the problems they are intended to solve. This separation confers to the user a maximum code and design reuse. Furthermore, the fine-grained nature of the classes provided by the framework allow a higher flexibility compared to other frameworks. ParadisEO is of the rare frameworks that provide the most common parallel and distributed models. Their implementation is portable on distributed-memory machines as well as on shared-memory multiprocessors, as it uses standard libraries such as MPI, PVM and PThreads. The models can be exploited in a transparent way, one has just to instantiate their associated provided classes. Their experimentation on the radio network design real-world application demonstrate their efficiency.


References in zbMATH (referenced in 34 articles , 1 standard article )

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  1. Greco, Salvatore (ed.); Ehrgott, Matthias (ed.); Figueira, José Rui (ed.): Multiple criteria decision analysis. State of the art surveys. In 2 volumes (2016)
  2. Tantar, Emilia; Palattella, Maria Rita; Avanesov, Tigran; Kantor, Miroslaw; Engel, Thomas: Cognition: a tool for reinforcing security in software defined networks (2014)
  3. Vidal, Thibaut; Crainic, Teodor Gabriel; Gendreau, Michel; Prins, Christian: A unified solution framework for multi-attribute vehicle routing problems (2014)
  4. Xie, Xiao-Feng; Liu, Jiming; Wang, Zun-Jing: A cooperative group optimization system (2014)
  5. Alba, Enrique; Luque, Gabriel; Nesmachnow, Sergio: Parallel metaheuristics: recent advances and new trends (2013)
  6. Aydemir, Fatma Başak; Günay, Akın; Öztoprak, Figen; İlker Birbil, Ş.; Yolum, Pınar: Multiagent cooperation for solving global optimization problems: an extendible framework with example cooperation strategies (2013)
  7. Marmion, Marie-Éléonore; Jourdan, Laetitia; Dhaenens, Clarisse: Fitness landscape analysis and metaheuristics efficiency (2013)
  8. Khanafer, Ali; Clautiaux, François; Hanafi, Saïd; Talbi, El-Ghazali: The min-conflict packing problem (2012)
  9. Khanafer, Ali; Clautiaux, François; Talbi, El-Ghazali: Tree-decomposition based heuristics for the two-dimensional bin packing problem with conflicts (2012)
  10. Kim, Jinwoo; Kim, Minyoung; Stehr, Mark-Oliver; Oh, Hyunok; Ha, Soonhoi: A parallel and distributed meta-heuristic framework based on partially ordered knowledge sharing (2012)
  11. Loukil, Lakhdar; Mehdi, Malika; Melab, Nouredine; Talbi, El-Ghazali; Bouvry, Pascal: Parallel hybrid genetic algorithms for solving Q3AP on computational grid (2012)
  12. Parejo, José Antonio; Ruiz-Cortés, Antonio; Lozano, Sebastián; Fernandez, Pablo: Metaheuristic optimization frameworks: a survey and benchmarking (2012)
  13. Benoist, Thierry; Estellon, Bertrand; Gardi, Frédéric; Megel, Romain; Nouioua, Karim: LocalSolver 1.x: A black-box local-search solver for 0-1 programming (2011)
  14. Liefooghe, Arnaud; Jourdan, Laetitia; Talbi, El-Ghazali: A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO (2011)
  15. Nikolakopoulos, Enrico Friedrich Pantelis G.; Papadopoulos, Christos I.; Kaiktsis, Lambros: Elastohydrodynamic analysis and Pareto optimization of intact, worn and misaligned journal bearings (2011)
  16. Puisa, Romanas; Streckwall, Heinrich: Prudent constraint-handling technique for multiobjective propeller optimisation (2011)
  17. Boisson, Jean-Charles; Jourdan, Laetitia; Talbi, El-Ghazali; Horvath, Dragos: Single- and multi-objective cooperation for the flexible docking problem (2010)
  18. Cole, Nate; Desell, Travis; Lombraña González, Daniel; Fernández De Vega, Francisco Fernández; Magdon-Ismail, Malik; Newberg, Heidi; Szymanski, Boleslaw; Varela, Carlos: Evolutionary algorithms on volunteer computing platforms: The MilkyWay@Home project (2010)
  19. Danoy, Grégoire; Bouvry, Pascal; Boissier, Olivier: A multi-agent organizational framework for coevolutionary optimization (2010)
  20. Figueira, J.R.; Liefooghe, A.; Talbi, E.-G.; Wierzbicki, A.P.: A parallel multiple reference point approach for multi-objective optimization (2010)

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Further publications can be found at: http://paradiseo.gforge.inria.fr/index.php?n=About.Publi