Extending Local Search in Geometric Semantic Genetic Programming

  • Mauro Castelli
  • Luca Manzoni
  • Luca MariotEmail author
  • Martina Saletta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11804)


In this paper we continue the investigation of the effect of local search in geometric semantic genetic programming (GSGP), with the introduction of a new general local search operator that can be easily customized. We show that it is able to obtain results on par with the current best-performing GSGP with local search and, in most cases, better than standard GSGP.



This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia) under project DSAIPA/DS/0022/2018 (GADgET).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mauro Castelli
    • 1
  • Luca Manzoni
    • 2
  • Luca Mariot
    • 2
    Email author
  • Martina Saletta
    • 1
  1. 1.NOVA Information Management School (NOVA IMS)Universidade Nova de LisboaLisbonPortugal
  2. 2.Dipartimento di Informatica Sistemistica e Comunicazione (DISCo)Università degli Studi di Milano BicoccaMilanItaly

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