Modified LSHADE-SPACMA with new mutation strategy and external archive mechanism for numerical optimization and point cloud registration

Abstract Numerical optimization and point cloud registration are critical research topics in the field of artificial intelligence. The differential evolution algorithm is an effective approach to address these problems, and LSHADE-SPACMA, the winning algorithm of CEC2017, is a competitive differential evolution variant. However, LSHADE-SPACMA’s local exploitation capability can sometimes be insufficient when handling these challenges. Therefore, in this work, we propose a modified version of LSHADE-SPACMA (mLSHADE-SPACMA) for numerical optimization and point cloud registration. Compared to the original approach, this work presents three main innovations. First, we present a precise elimination and generation…

• NN
  National Natural Science Foundation of China

  Award: 52165063
• GS
  Guizhou Science and Technology Department

  Awards: 006-1, Qiankehe pingtai rencai-CXTD [2023] No.007, Qiankehe pingtai rencai-GCC [2022] No.006-1
• NS
  Natural Science Foundation of Chongqing

  Awards: CSTB2022NSCQ, CSTB2022NSCQ-MSX1600
• CS
  Centre Scientifique et Technique du Bâtiment
• DO
  Division of Graduate Education