GENETIC ALGORITHM VERSUS ANT COLONY OPTIMIZATION ALGORITHM - Comparison of Performances in Robot Path Planning Application

Abstract

This paper presents the results of a research that uses a simulation approach to compare the effectiveness and efficiency of two path planning algorithms. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) Algorithm for Robot Path Planning (RPP) were tested in a global static environment. Both algorithms were applied within a global map that provides feasible nodes from start point to goal. Performances between both algorithms were compared and evaluated in terms of computational efficiency by measuring the speed and number of iterations, accuracy of solution, solution variation and convergence behavior.