Advanced dwarf mongoose optimization for solving CEC 2011 and CEC 2017 benchmark problems.

ABSTRACT: This paper proposes an improvement to the dwarf mongoose optimization (DMO) algorithm called the advanced dwarf mongoose optimization (ADMO) algorithm. The improvement goal is to solve the low convergence rate limitation of the DMO. This situation arises when the initial solutions are close to the optimal global solution; the subsequent value of the alpha must be small for the DMO to converge towards a better solution. The proposed improvement incorporates other social behavior of the dwarf mongoose, namely, the predation and mound protection and the reproductive and group splitting behavior to enhance the exploration and exploitation ability of the DMO. The ADMO also modifies the lifestyle of the alpha and subordinate group and the foraging and seminomadic behavior of the DMO. The propose

SUBMITTER: Agushaka JO 

PROVIDER: S-EPMC9629639 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature