Age distribution adjustments in human resource department using shuffled frog leaping algorithm

Abstract

Shuffled frog leaping (SFL) algorithm is a recently introduced member of memetic algorithms family. It inherits the features of Particle Swarm Optimization and Shuffled Complex Evolution algorithms. Its intensification component of search is similar to Particle Swarm Optimization while the inspiration for diversification is inherited from the global exchange of information in Shuffled Complex Evolution. In this study SFL algorithm is implemented to a discrete problem of human resources distribution as per the present age group to the desired age group distribution. This problem is a challenging part of human resource planning in human resource department of an organization. The simulated results presents that SFL algorithm is able to find optimal adjustment magnitudes of the employees at the selected age groups. The results are also compared with Genetic algorithm.