Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems

Abstract Solving nonlinear equation systems (NESs) requires locating different roots in one run. To effectively deal with NESs, a multi-population cooperative teaching–learning-based optimization, named MCTLBO, is presented. The innovations of MCTLBO are as follows: (i) two niching technique (crowding and improved speciation) integrated into the algorithm to enhance population diversity; (ii) an adaptive selection scheme proposed select learning rules teaching phase; (iii) new based on experience developed promote search efficiency phases. was tested 30 classical problems experimental results show that has better root finding performance than other algorithms. In addition, achieves competitive eighteen test sets.