• Balázs Bánhelyi
  • Tibor Csendes
  • Balázs Lévai
  • László Pál
  • Dániel Zombori
Part of the SpringerBriefs in Optimization book series (BRIEFSOPTI)


Nowadays, solving global optimization problems is a crucial and inescapable part of the daily operation of almost every branch of natural sciences and the modern industry. The scale and variety of problems are larger than ever. For some time, providing efficient tools for these tasks is not just a challenge for researchers, it is an ever-growing expectation from the stakeholders of the tech industry and indirectly from the information society. In our book, we revisit GLOBAL, a stochastic optimization method aiming to solve nonlinear, bound constrained optimization problems. It is a versatile tool for a broad range of problems, proven to be competitive in multiple comparisons. To extend usability, now we present a Java implementation, GLOBALJ. It is an entire, modularized framework extending the potential of this algorithm.


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Copyright information

© The Author(s), under exclusive licence to Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Balázs Bánhelyi
    • 1
  • Tibor Csendes
    • 1
  • Balázs Lévai
    • 2
  • László Pál
    • 3
  • Dániel Zombori
    • 1
  1. 1.Department of Computational OptimizationUniversity of SzegedSzegedHungary
  2. 2.NNG IncSzegedHungary
  3. 3.Sapientia Hungarian University of TransylvaniaMiercurea CiucRomania

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