The problem of determining the minimum motion time for a robot arm is not new. Several approaches have been successfully proposed to solve this problem. One of these approaches involves generating a fixed number of joint displacements to construct the joint trajectories via cubic spline functions before scaling the travel time to avoid violating kinematic constraints such as the maximum permissible velocity, acceleration and jerk. Conforming to these kinematic constraints is necessary to prevent trajectories that are undulant and normally unsuitable for robotic motion. This paper presents a Pareto-based multi-objective Bees Algorithm to determine the minimum travelling time for a SCARA-type robot arm that takes consideration of trajectory smoothness. The results obtained are better than those reported for solutions using the genetic algorithm (with breeder genetic algorithm operators and the path redistribution with relaxation operator), the Nelder-Mead flexible polyhedron search and the improved polytope algorithm with a penalty function.