A Modified Honey Badger Algorithm with Logistic Map and Enhanced Exploitation

Nature-inspired algorithms are useful tools for optimization. Metaheuristic characteristics of these algorithms make them applicable to almost all problems with limited information available. The Honey Badger Algorithm is a recently introduced algorithm yielding its inspiration from the foraging behavior of honey badgers. This paper proposes two modifications to enhance the performance of this algorithm. The first modification is to use the logistic map in population initialization. The second one is the introduction of an exploitation operation in the honey phase. To control the degree of exploitation, the paper proposes a variable called Exploitation Rate (ER). The proposal has been used to optimize a set of 23 diverse test functions and has been analyzed with various values of ER. The proposed variant has also been implemented to optimize the 25-bar truss design problem.