SOMA, and generally speaking any evolutionary algorithm, can be used in regards to any optimization problem. Surprisingly, many problems can be defined as optimization problems, e.g. the optimal trajectory of robot arms; the optimal thickness of steel in pressure vessels; the optimal set of parameters for controllers; optimal relations or fuzzy sets in fuzzy models; and so on. Solutions to such problems are usually more or less hard to arrive at, their parameters usually including variables of different types, such as real or integer variables. Evolutionary algorithms are quite popular because they allow the solution of almost any problem in a simplified manner, because they are able to handle optimizing tasks with mixed variables - including the appropriate constraints, as and when required

References in zbMATH (referenced in 21 articles , 1 standard article )

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  1. Nash, John C.: Nonlinear parameter optimization using R tools (2014)
  2. Pluhacek, Michal; Senkerik, Roman; Zelinka, Ivan: Particle swarm optimization algorithm driven by multichaotic number generator (2014)
  3. Senkerik, Roman; Oplatkova, Zuzana Kominkova; Zelinka, Ivan; Chramcov, Bronislav; Davendra, Donald D.; Pluhacek, Michal: Utilization of analytic programming for the evolutionary synthesis of the robust multi-chaotic controller for selected sets of discrete chaotic systems (2014)
  4. Davendra, Donald; Zelinka, Ivan; Bialic-Davendra, Magdalena; Senkerik, Roman; Jasek, Roman: Discrete Self-Organising Migrating Algorithm for flow-shop scheduling with no-wait makespan (2013)
  5. Davendra, Donald; Zelinka, Ivan; Senkerik, Roman: Chaos driven evolutionary algorithms for the task of PID control (2010)
  6. Senkerik, Roman; Zelinka, Ivan; Davendra, Donald; Oplatkova, Zuzana: Utilization of SOMA and differential evolution for robust stabilization of chaotic logistic equation (2010)
  7. Senkerik, Roman; Zelinka, Ivan; Davendra, Donald; Oplatkova, Zuzana: Evolutionary design of chaos control in 1D (2010)
  8. Zelinka, Ivan; Jasek, Roman: Evolutionary decryption of chaotically encrypted information (2010)
  9. Dos Santos Coelho, Leandro: Self-organizing migration algorithm applied to machining allocation of clutch assembly (2009)
  10. Mariani, Viviana Cocco; dos Santos Coelho, Leandro: Global optimization of thermal conductivity using stochastic algorithms (2009)
  11. Zelinka, Ivan; Senkerik, Roman; Navratil, Eduard: Investigation on evolutionary optimization of chaos control (2009)
  12. Deep, Kusum; Dipti: A self-organizing migrating genetic algorithm for constrained optimization (2008)
  13. Zelinka, Ivan; Chen, Guanrong; Celikovsky, Sergej: Chaos synthesis by means of evolutionary algorithms (2008)
  14. Arhin, John: On the structure of 1-designs with at most two block intersection numbers (2007)
  15. Bailey, R.A.; Cameron, Peter J.: What is a design? how should we classify them? (2007)
  16. ńĆervenka, Miroslav; Zelinka, Ivan: Relay node placement in energy-constrained networks using SOMA evolutionary algorithm (2006)
  17. Durrant, Simon; Feng, Jianfeng: Negatively correlated firing: the functional meaning of lateral inhibition within cortical columns (2006)
  18. Berlekamp, Elwyn R.; Conway, John H.; Guy, Richard K.: Winning ways for your mathematical plays. Vol. 4 (2004)
  19. Zelinka, Ivan: SOMA -- self-organizing migrating algorithm (2004)
  20. Zelinka, Ivan; Lampinen, Jouni: Mechanical engineering problem optimization by SOMA (2004)

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