PERL

Programming Perl. Perl is a language for easily manipulating text, files, and processes. Perl provides a more concise and readable way to do many jobs that were formerly accomplished (with difficulty) by programming in the C language or one of the shells. While this book is primarily intended for users of the UNIX operating system, Perl runs on several other operating systems, and provides a portable model of computing across diverse architectures. (wikipedia)


References in zbMATH (referenced in 176 articles , 3 standard articles )

Showing results 1 to 20 of 176.
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  1. Napoletano, Antonio; Martínez-Gavara, Anna; Festa, Paola; Pastore, Tommaso; Martí, Rafael: Heuristics for the constrained incremental graph drawing problem (2019)
  2. Zhou, Qing; Benlic, Una; Wu, Qinghua; Hao, Jin-Kao: Heuristic search to the capacitated clustering problem (2019)
  3. de Holanda Maia, Marcelo Rodrigues; Plastino, Alexandre; Penna, Puca Huachi Vaz: Hybrid data mining heuristics for the heterogeneous fleet vehicle routing problem (2018)
  4. Martins, Daniel; Vianna, Gabriel M.; Rosseti, Isabel; Martins, Simone L.; Plastino, Alexandre: Making a state-of-the-art heuristic faster with data mining (2018)
  5. Pinto, Bruno Q.; Ribeiro, Celso C.; Rosseti, Isabel; Plastino, Alexandre: A biased random-key genetic algorithm for the maximum quasi-clique problem (2018)
  6. Reyes, Alberto; Ribeiro, Celso C.: Extending time-to-target plots to multiple instances (2018)
  7. Richard Beare; Bradley Lowekamp; Ziv Yaniv: Image Segmentation, Registration and Characterization in R with SimpleITK (2018) not zbMATH
  8. Tunga, Burcu: A hybrid algorithm with cluster analysis in modelling high dimensional data (2018)
  9. Wicke, Kristina; Fischer, Mareike: Phylogenetic diversity and biodiversity indices on phylogenetic networks (2018)
  10. Berman, Abraham (ed.); Bomze, Immanuel M. (ed.); Dür, Mirjam (ed.); Shaked-Monderer, Naomi (ed.): Copositivity and complete positivity. Abstracts from the workshop held October 29 -- Novermber 4, 2017 (2017)
  11. Groz, B.; Maneth, S.: Efficient testing and matching of deterministic regular expressions (2017)
  12. Levorato, Mario; Figueiredo, Rosa; Frota, Yuri; Drummond, Lúcia: Evaluating balancing on social networks through the efficient solution of correlation clustering problems (2017)
  13. Máximo, Vinícius R.; Nascimento, Mariá C. V.; Carvalho, André C. P. L. F.: Intelligent-guided adaptive search for the maximum covering location problem (2017)
  14. Wang, Yang; Wu, Qinghua; Glover, Fred: Effective metaheuristic algorithms for the minimum differential dispersion problem (2017)
  15. Bastos, Rafaela; Broda, Sabine; Machiavelo, António; Moreira, Nelma; Reis, Rogério: On the state complexity of partial derivative automata for regular expressions with intersection (2016)
  16. Berk Ekmekci, Charles E. McAnany, Cameron Mura: An Introduction to Programming for Bioscientists: A Python-based Primer (2016) arXiv
  17. Brandão, Julliany S.; Noronha, Thiago F.; Ribeiro, Celso C.: A biased random-key genetic algorithm to maximize the number of accepted lightpaths in WDM optical networks (2016)
  18. Chaves, A. A.; Lorena, L. A. N.; Senne, E. L. F.; Resende, M. G. C.: Hybrid method with CS and BRKGA applied to the minimization of tool switches problem (2016)
  19. Coelho, V. N.; Grasas, A.; Ramalhinho, H.; Coelho, I. M.; Souza, M. J. F.; Cruz, R. C.: An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints (2016)
  20. De Santis, M.; Festa, P.; Liuzzi, G.; Lucidi, S.; Rinaldi, F.: A nonmonotone GRASP (2016)

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