In the field of computational mathematics, direct search algorithm has a greater role in solving optimization and decision-making problems. In this direction, many algorithms have been developed to solve the optimization problems, and these algorithms are classified into two major categories: Evolutionary Algorithms (Genetic Algorithm, Differential Evolution, etc.) and Swarm Intelligence (Particle Swarm Algorithm, Ant Colony Algorithm, etc.). In Swarm Intelligence Algorithms, the behaviour of a population in a group of particles or individuals is observed and the pattern of transferring the information from the particle of the previous generation to the new generation is obtained through mathematical expressions and logical progression of the algorithm. In the present paper, an attempt has been made to develop a swarm intelligence algorithm by following the behaviour of root hair searching underground water for the plant. The algorithm is coded in SciLab 6.1.0 and 15 experimental problems are selected from Jamil et al. (2013) to test the algorithm. A fair comparison has been made with the MEAN \(\pm\) SD for the selected problem adopted from (Wahab et al. in PLoS ONE 10, 2015) by standard algorithms such as Particle Swarm Optimization, Ant Colony Algorithm, Genetic Algorithm and Differential Evolution.